2943 lines
983 KiB
Text
2943 lines
983 KiB
Text
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "8aed3e97",
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"metadata": {},
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"outputs": [],
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"source": [
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"from functools import reduce\n",
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"\n",
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"import numpy as np\n",
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"\n",
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"import cantera as ct\n",
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"\n",
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"import matplotlib.ticker \n",
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"from matplotlib import pyplot as plt\n",
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"%matplotlib widget"
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]
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},
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{
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"cell_type": "markdown",
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"id": "fd1817d3",
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"metadata": {},
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"source": [
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"# 탄화실 나이 분포"
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]
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},
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{
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"cell_type": "markdown",
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"id": "9c64324b",
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"metadata": {},
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"source": [
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"## 장입-추출 시퀀스\n",
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"\n",
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"$n$ 번 건류실 추출/장입 후 $n+5$ 번 건류실에 추출/장입\n",
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"* 1 번에서 시작시 66번까지 진행 이후 3 번에서 시작. $ 1, 6, 11, \\ldots , 66 $\n",
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"* 3 번에서 63번까지 진행 이후 5 번에서 시작. $ 3, 6, 11, \\ldots , 63 $\n",
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"* 5 번에서 65번까지 진행 이후 2 번에서 시작. $ 5, 6, 11, \\ldots , 65 $\n",
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"* 2 번에서 62번까지 진행 이후 4 번에서 시작. $ 2, 6, 11, \\ldots , 62 $\n",
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"* 4 번에서 64번까지 진행 이후 다시 1 번에서 시작. $ 4, 9, 14, \\ldots , 64 $\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "de03e1d6",
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"metadata": {},
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"source": [
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"### 탄화실 별 장입 시기"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "99dd258f",
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"metadata": {},
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"outputs": [],
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"source": [
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"n_oven = 66\n",
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"\n",
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"oven_idx_sequence = np.zeros(n_oven)\n",
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"\n",
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"start_indices = [1, 3, 5, 2, 4]\n",
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"\n",
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"i_order = 0\n",
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"for idx0 in np.array(start_indices)-1:\n",
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" for idx in range(idx0, n_oven, 5):\n",
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" oven_idx_sequence[idx] = i_order\n",
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" i_order += 1"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "125f87b0",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<StemContainer object of 3 artists>"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "328be3db1f424c50bc8707af134473f2",
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"version_major": 2,
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"version_minor": 0
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},
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"image/png": 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"\n",
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" <div style=\"display: inline-block;\">\n",
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" <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
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" Figure\n",
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" </div>\n",
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' width=640.0/>\n",
|
|
" </div>\n",
|
|
" "
|
|
],
|
|
"text/plain": [
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.figure()\n",
|
|
"plt.stem(66 - oven_idx_sequence)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"id": "8c76eb74",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<StemContainer object of 3 artists>"
|
|
]
|
|
},
|
|
"execution_count": 4,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"application/vnd.jupyter.widget-view+json": {
|
|
"model_id": "90aa50be49884adbbf4fdb4443d749ee",
|
|
"version_major": 2,
|
|
"version_minor": 0
|
|
},
|
|
"image/png": 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",
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' width=640.0/>\n",
|
|
" </div>\n",
|
|
" "
|
|
],
|
|
"text/plain": [
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.figure()\n",
|
|
"plt.stem(np.abs(np.diff(66 - oven_idx_sequence)))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "70ca2659",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 연소실 양쪽 탄화실 평균 나이"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 5,
|
|
"id": "910a4ec1",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<StemContainer object of 3 artists>"
|
|
]
|
|
},
|
|
"execution_count": 5,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"application/vnd.jupyter.widget-view+json": {
|
|
"model_id": "27c5716a21a44695ba64a50eefc2cea9",
|
|
"version_major": 2,
|
|
"version_minor": 0
|
|
},
|
|
"image/png": 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"\n",
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" <div style=\"display: inline-block;\">\n",
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" <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
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" Figure\n",
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" </div>\n",
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' width=640.0/>\n",
|
|
" </div>\n",
|
|
" "
|
|
],
|
|
"text/plain": [
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.figure()\n",
|
|
"plt.stem(((66 - oven_idx_sequence)[:-1] + (66 - oven_idx_sequence)[1:])/2)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 6,
|
|
"id": "6b18807d",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"n_oven = 66\n",
|
|
"\n",
|
|
"start_indices = [1, 3, 5, 2, 4]\n",
|
|
"\n",
|
|
"oven_idx_order = np.concatenate([np.array(range(i0 - 1, n_oven, 5)) for i0 in start_indices])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 7,
|
|
"id": "1007d82d",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
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"data": {
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"text/plain": [
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"66"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"oven_idx_order.size"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "3fc5bccd",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([ 0, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 2, 7, 12,\n",
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" 17, 22, 27, 32, 37, 42, 47, 52, 57, 62, 4, 9, 14, 19, 24, 29, 34,\n",
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" 39, 44, 49, 54, 59, 64, 1, 6, 11, 16, 21, 26, 31, 36, 41, 46, 51,\n",
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" 56, 61, 3, 8, 13, 18, 23, 28, 33, 38, 43, 48, 53, 58, 63])"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"oven_idx_order"
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]
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},
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{
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"cell_type": "markdown",
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"id": "9fb0a4f4",
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"metadata": {},
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"source": [
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"# 코크 오븐 모델"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"id": "37a3a13f",
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"metadata": {},
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"outputs": [],
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"source": [
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"class Battery:\n",
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" \n",
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" def __init__ (self, name, size, heat_program, charge_program, T_combustion_0):\n",
|
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" self.name = name\n",
|
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" self.size = size\n",
|
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" self.heat_program = heat_program\n",
|
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" self.charge_program = charge_program\n",
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" self.t = 0\n",
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" self.t_last = 0\n",
|
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" self.processing = []\n",
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" self.product = []\n",
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" self.T0 = T_combustion_0\n",
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" self.sequence_idx = 0\n",
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" \n",
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" # For 1~4 Coke Ovens with n+5 PC sequence\n",
|
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" start_indices = [1, 3, 5, 2, 4]\n",
|
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" self.oven_idx_order = np.concatenate([np.array(range(i0 - 1, self.size, 5)) for i0 in start_indices])\n",
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"\n",
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" # 정상 상태 만들기: 모든 문에 n_cycle 회 장입\n",
|
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" n_cycle = 3 # 모든 문 장입 반복 횟수\n",
|
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" period_over_dt = 11. # 장입 간격 / 초기화 time step 크기\n",
|
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" normal_period = self.charge_program.period(-1)\n",
|
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" dt = normal_period / period_over_dt\n",
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" \n",
|
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" self.t = - normal_period * self.size * n_cycle # 정상상태 생성 모사 시간 = 장입 간격 * 총 장입 횟수\n",
|
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" self.t_last = self.t # 마지막 장입을 정상상태 시뮬레이션 시작 시각으로 설정\n",
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" \n",
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" # time loop\n",
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" for i in range(int(np.ceil(self.size * period_over_dt * n_cycle))):\n",
|
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" \"\"\" Fill battety with normal charge rate \"\"\"\n",
|
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" self.update(dt)\n",
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"\n",
|
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" def next_oven (self):\n",
|
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" next_oven_id = self.oven_idx_order[self.sequence_idx % self.size]\n",
|
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" self.sequence_idx += 1\n",
|
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" return next_oven_id\n",
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"\n",
|
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" def bake (self, dt):\n",
|
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" # update combustion chamber equilibrium temperature\n",
|
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" # Tad = 연료 조성과 공연비로 결정\n",
|
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" # m_dot = 연료 발열량과 공급열량 공연비로 결정\n",
|
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" # m(h1 - h0) = hA(Tgas - Twall) => solve with initial T0 = Tad\n",
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" \n",
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" # advance time oven brick\n",
|
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" # from chamber heat flux boundary condition\n",
|
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" # to oven fixed temperature boundary condition\n",
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" \n",
|
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" # integrate heat to oven # 오븐 벽면 온도 우선 시간 함수로\n",
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"\n",
|
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" dQ = self.dQ(dt) # array, dQ pairs of all oven taking from both walls\n",
|
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" \n",
|
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" for cc in self.processing:\n",
|
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" cc.bake(dQ) # bake.(dQ[cc.idx_oven])\n",
|
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"\n",
|
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" def push_and_charge (self, coke_charge):\n",
|
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" if len(self.processing) >= self.size:\n",
|
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" self.push()\n",
|
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" self.charge(coke_charge)\n",
|
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" \n",
|
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" def push (self):\n",
|
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" \"\"\" Push complete coke out of oven \"\"\"\n",
|
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" coke = self.processing.pop(0)\n",
|
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" coke.end_baking(self.t)\n",
|
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" self.product.append(coke)\n",
|
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"\n",
|
|
" def charge (self, coke_charge):\n",
|
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" self.processing.append(coke_charge)\n",
|
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"\n",
|
|
" def dQ (self, dt):\n",
|
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" return self.heat_program.dQ(self.t, self.t+dt)\n",
|
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" \n",
|
|
" def is_pc_time (self, dt):\n",
|
|
" return self.t + dt >= period + self.t_last\n",
|
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"\n",
|
|
" def update (self, dt):\n",
|
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" # dQ = self.heat_program.dQ(self.t, self.t+dt) # t, t+dt 사이 공급하는 열량, array 로 대체 필요\n",
|
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" \n",
|
|
" # t 에서 t+dt 까지 탄화실 가열\n",
|
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" self.bake(dt)\n",
|
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" \n",
|
|
" period = self.charge_program.period(self.t) # 현재 장입 시간 간격\n",
|
|
" \n",
|
|
" # 마지막 장입탄 장입 시각\n",
|
|
" latest_coke_charge = self.processing[-1].t_charge if len(self.processing) > 0 else self.t_last\n",
|
|
" \n",
|
|
" # t_last + period 가 t, t + dt 사이에 들어오는 것 검사\n",
|
|
" # t + dt 가 다음 추출/장입 시각 이후일 때 => 이번 time step 에 추출/장입을 실행해야함\n",
|
|
" if self.t + dt >= period + self.t_last :\n",
|
|
" print(\"Push timing within [ {} , {} ].\".format(self.t, self.t + dt), \n",
|
|
" self.t + dt - latest_coke_charge, \"since last P/C. \", \n",
|
|
" \"P/C interval = \", self.charge_program.period(self.t),)\n",
|
|
" \n",
|
|
" # 마지막 장입 시각 + 장입 시간 간격 이 이번 time step 에 포함됨\n",
|
|
" # 일정한 간격으로 장입 진행 중\n",
|
|
" if self.t < self.t_last + period:\n",
|
|
" self.t_last += period\n",
|
|
" # 마지막 장입 이후 현재 장입 간격보다 긴 시간이 경과함\n",
|
|
" # 이번 time step 끝을 마지막 장입 시각으로 업데이트\n",
|
|
" else:\n",
|
|
" self.t_last = self.t + dt\n",
|
|
" \n",
|
|
" # 추출/장입 실행\n",
|
|
" self.push_and_charge(CokeCharge(self.t + dt, self.next_oven()))\n",
|
|
" \n",
|
|
" # 시뮬레이션 시간 업데이트\n",
|
|
" self.t += dt\n",
|
|
"\n",
|
|
"\n",
|
|
"class CokeCharge:\n",
|
|
" \n",
|
|
" def __init__ (self, t_charge, idx_oven):\n",
|
|
" self.t_charge = t_charge\n",
|
|
" self.t_push = None\n",
|
|
" self.idx_oven = idx_oven\n",
|
|
" self.Q = 0\n",
|
|
"\n",
|
|
" def bake (self, dQ):\n",
|
|
" self.Q += dQ\n",
|
|
" \n",
|
|
" def end_baking (self, t):\n",
|
|
" self.t_push = t\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "5dde8174",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 엑셀 매크로 결과 정수 감급 계획"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 10,
|
|
"id": "070094b4",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sample_program = np.array('''\\\n",
|
|
"-3\t81\n",
|
|
"0\t81\n",
|
|
"0\t69.61621622\n",
|
|
"3.5\t69.61621622\n",
|
|
"3.5\t58.83157895\n",
|
|
"7\t58.83157895\n",
|
|
"7\t48.6\n",
|
|
"10.5\t48.6\n",
|
|
"10.5\t42.039\n",
|
|
"14.5\t42.039\n",
|
|
"14.5\t38.88\n",
|
|
"24.5\t38.88\n",
|
|
"24.5\t42.039\n",
|
|
"27.75\t42.039\n",
|
|
"27.75\t48.6\n",
|
|
"30.35\t48.6\n",
|
|
"30.35\t58.83157895\n",
|
|
"32.43\t58.83157895\n",
|
|
"32.43\t69.61621622\n",
|
|
"34.094\t69.61621622\n",
|
|
"34.094\t81\n",
|
|
"36.46688136\t81\n",
|
|
"36.46688136\t72.9\n",
|
|
"39.46688136\t72.9\n",
|
|
"39.46688136\t67.23\n",
|
|
"42.46688136\t67.23\n",
|
|
"42.46688136\t62.37\n",
|
|
"47.46688136\t62.37\n",
|
|
"47.46688136\t67.23\n",
|
|
"50.46688136\t67.23\n",
|
|
"50.46688136\t72.9\n",
|
|
"53.46688136\t72.9\n",
|
|
"53.46688136\t81\n",
|
|
"56.46688136\t81\n",
|
|
"'''.split(), dtype=np.double).reshape((-1,2))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 11,
|
|
"id": "bc714fba",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"[<matplotlib.lines.Line2D at 0x1fddd477970>]"
|
|
]
|
|
},
|
|
"execution_count": 11,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"application/vnd.jupyter.widget-view+json": {
|
|
"model_id": "0657d5d05e064af1993afe40df8530e2",
|
|
"version_major": 2,
|
|
"version_minor": 0
|
|
},
|
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"image/png": 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",
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"\n",
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" <div style=\"display: inline-block;\">\n",
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" <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
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" Figure\n",
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" </div>\n",
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' width=640.0/>\n",
|
|
" </div>\n",
|
|
" "
|
|
],
|
|
"text/plain": [
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"sample_time = np.linspace(-9, 72, 1000)\n",
|
|
"plt.figure()\n",
|
|
"plt.plot(sample_time / 60., np.interp(sample_time, *sample_program.T), '-o')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "a2665c72",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 이전 정수 계획 중 가져옴\n",
|
|
"정수 감/증급 단계와 추가감산 감/증급 단계의 중첩 있음"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 12,
|
|
"id": "9713bb3a",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"example_program = np.array([\n",
|
|
"-600 , 0,\n",
|
|
"-360 , 0,\n",
|
|
"-360 , -6.8,\n",
|
|
"-280 , -6.8,\n",
|
|
"-280 , -6.8 -6.63,\n",
|
|
"-180 , -6.8 -6.63,\n",
|
|
"-180 , -6.8 -6.63 -6.8,\n",
|
|
"-120 , -6.8 -6.63 -6.8,\n",
|
|
"-120 , -6.8 -6.63 -6.8 -6.35,\n",
|
|
"-40 , -6.8 -6.63 -6.8 -6.35,\n",
|
|
"-40 , -6.8 -6.63 -6.8 -6.35 -6.18,\n",
|
|
"9*60 + 80 , -6.8 -6.63 -6.8 -6.35 -6.18,\n",
|
|
"9*60 + 80 , -6.8 -6.63 -6.8 -6.35,\n",
|
|
"9*60 + 240 , -6.8 -6.63 -6.8 -6.35,\n",
|
|
"9*60 + 240 , -6.8 -6.63 -6.8,\n",
|
|
"9*60 + 480 , -6.8 -6.63 -6.8,\n",
|
|
"9*60 + 480 , -6.8 -6.63,\n",
|
|
"9*60 + 720 , -6.8 -6.63,\n",
|
|
"9*60 + 720 , -6.8,\n",
|
|
"9*60 + 960 , -6.8,\n",
|
|
"9*60 + 960 , 0,\n",
|
|
"9*60 + 1200 , 0,\n",
|
|
"(15+13)*60 + -300 -240 , 0,\n",
|
|
"(15+13)*60 + -240 , 0,\n",
|
|
"(15+13)*60 + -240 , - 5.46,\n",
|
|
"(15+13)*60 + -180 , - 5.46,\n",
|
|
"(15+13)*60 + -180 , - 5.46 - 5.25,\n",
|
|
"(15+13)*60 + -120 , - 5.46 - 5.25,\n",
|
|
"(15+13)*60 + -120 , - 5.46 - 5.25 - 5.14,\n",
|
|
"(15+13)*60 + -40 , - 5.46 - 5.25 - 5.14,\n",
|
|
"(15+13)*60 + -40 , - 5.46 - 5.25 - 5.14 - 4.31,\n",
|
|
"(15+13)*60 + 3*60 + 40 , - 5.46 - 5.25 - 5.14 - 4.31,\n",
|
|
"(15+13)*60 + 3*60 + 40 , - 5.46 - 5.25 - 5.14,\n",
|
|
"(15+13)*60 + 3*60 + 180 , - 5.46 - 5.25 - 5.14,\n",
|
|
"(15+13)*60 + 3*60 + 180 , - 5.46 - 5.25,\n",
|
|
"(15+13)*60 + 3*60 + 280 , - 5.46 - 5.25,\n",
|
|
"(15+13)*60 + 3*60 + 280 , - 5.46,\n",
|
|
"(15+13)*60 + 3*60 + 360 , - 5.46,\n",
|
|
"(15+13)*60 + 3*60 + 360 , 0,\n",
|
|
"(15+13)*60 + 3*60 + 360 + 300 , 0,\n",
|
|
"]).reshape((-1, 2)).T\n",
|
|
"\n",
|
|
"example_program[0] /= 60.\n",
|
|
"example_program[0] += 9.\n",
|
|
"example_program[1] += 73."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 13,
|
|
"id": "22a6d66f",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"[<matplotlib.lines.Line2D at 0x1fddd4e67c0>]"
|
|
]
|
|
},
|
|
"execution_count": 13,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"application/vnd.jupyter.widget-view+json": {
|
|
"model_id": "a5edbfdc4ab34e3cb913085dc17e74e0",
|
|
"version_major": 2,
|
|
"version_minor": 0
|
|
},
|
|
"image/png": 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",
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"\n",
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" <div style=\"display: inline-block;\">\n",
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" <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
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" Figure\n",
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" </div>\n",
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' width=640.0/>\n",
|
|
" </div>\n",
|
|
" "
|
|
],
|
|
"text/plain": [
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"sample_time = np.linspace(-9, 72, 1000)\n",
|
|
"plt.figure()\n",
|
|
"plt.plot(sample_time, np.interp(sample_time, *example_program), '-o')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 14,
|
|
"id": "55d32e63",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"[<matplotlib.lines.Line2D at 0x1fddd558c10>]"
|
|
]
|
|
},
|
|
"execution_count": 14,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"application/vnd.jupyter.widget-view+json": {
|
|
"model_id": "9538a5a9f94b45269fad944c5403c8f5",
|
|
"version_major": 2,
|
|
"version_minor": 0
|
|
},
|
|
"image/png": 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",
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"\n",
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" <div style=\"display: inline-block;\">\n",
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" <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
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" Figure\n",
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" </div>\n",
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" <img 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' width=640.0/>\n",
|
|
" </div>\n",
|
|
" "
|
|
],
|
|
"text/plain": [
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.figure()\n",
|
|
"plt.plot(*example_program)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "67f35bad",
|
|
"metadata": {},
|
|
"source": [
|
|
"# 정수 계획 클래스\n",
|
|
"Battety 클래스에 대한 인터페이스 제공"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 15,
|
|
"id": "37299004",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"class HeatSchedule:\n",
|
|
" def __init__ (self, xp, fp):\n",
|
|
" self.xp = xp\n",
|
|
" self.fp = fp\n",
|
|
" self.f = lambda x: np.interp(x, self.xp, self.fp)\n",
|
|
" \n",
|
|
" def dQ(self, t0, t1):\n",
|
|
" x = np.linspace(t0, t1, 31)\n",
|
|
" return np.trapz(self.f(x), x) "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 16,
|
|
"id": "1322ad78",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"class ChargeSchedule:\n",
|
|
" def __init__ (self, normal_load, service_start, service_time, service_load, aux_start, aux_time, aux_load):\n",
|
|
" self.xp = np.array([service_start, service_start, service_start+service_time, service_start+service_time, \n",
|
|
" aux_start, aux_start, aux_start+aux_time, aux_start+aux_time, ])\n",
|
|
" self.fp = np.array([normal_load, service_load, service_load, normal_load,\n",
|
|
" normal_load, aux_load, aux_load, normal_load])\n",
|
|
" self.f = lambda x: np.interp(x, self.xp, self.fp)\n",
|
|
" \n",
|
|
" def to_charge (self, t0, t1):\n",
|
|
" self.f(t0)\n",
|
|
" return np.trapz(self.f(x), x)\n",
|
|
" \n",
|
|
" def period (self, t):\n",
|
|
" return 24 / self.f(t)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 17,
|
|
"id": "69ab56fc",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sample_schedule = HeatSchedule(*sample_program.T)\n",
|
|
"sample_schedule2 = HeatSchedule(*example_program)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "93094db8",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 엑셀 매크로 결과의 정수 계획 및 추가감산 "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 18,
|
|
"id": "6d6eac92",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sample_charging = ChargeSchedule( 81, 9, 9, 1e-12, 24+13, 3, 1e-12 )"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 19,
|
|
"id": "e742dad8",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"[<matplotlib.lines.Line2D at 0x1fdddd67a90>]"
|
|
]
|
|
},
|
|
"execution_count": 19,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"application/vnd.jupyter.widget-view+json": {
|
|
"model_id": "4866bd88aaca446d8dd59a743cfdf663",
|
|
"version_major": 2,
|
|
"version_minor": 0
|
|
},
|
|
"image/png": 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",
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"\n",
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" Figure\n",
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ers7MxhxfAj7gWMbErnxZuZawDJOBsA+/v7df3112vGjBl64YUXdODAAX3rW9/Sxz72scRrGhoa1NjYqObmZnV0dCgajaqqqkpDQ0O5Kxy+ZfvOStt3MQfNlGaLqQbgIS/XBWTKN77xDZWWlmrr1q2JY5dcckniv40xampq0oYNG7Ry5UpJ0rZt2xSJRLR9+3bdd9992S4ZAAAgK5xdAXz++ee1cOFC3X777Zo1a5auueYabdmyJfF8V1eXent7VV1dnTgWDoe1ZMkStbe356Jk+JRrXTTXxuOadLZtXTt9AUD6OBsADx48qE2bNqm8vFwvvfSS7r//fj344IN68sknJUm9vb2SpEgkMu77IpFI4rlTDQ8Pa3BwcNwDwWH7zkq7qw+eqe0CBoDJOdsCHhsb08KFC1VXVydJuuaaa9TZ2alNmzbp7rvvTrzu1N+QjTFJf2uur6/Xxo0bM1c0AABAFji7Ajh79mzNnTt33LErr7xShw4dkiRFo1FJmrDa19fXN2FVMK62tlYDAwOJR09PTwYqh++k4bpsfhCvn7agv6VjduIbfphpAMk4GwCvv/56vfXWW+OOvf3227r44oslSWVlZYpGo2ptbU08PzIyora2NlVWVp72Z4bDYRUVFY17AEAm2H7KAQB/c7YF/Gd/9meqrKxUXV2d/vAP/1A//elPtXnzZm3evFnSiVWQmpoa1dXVqby8XOXl5aqrq1NBQYFWrVqV4+rhJ+m8LpsfuDUaTIrJBpCEswHw2muv1bPPPqva2lp97WtfU1lZmZqamnTXXXclXrN+/XodO3ZMa9asUX9/vxYtWqSWlhYVFhbmsHL4lf3rMfaPIAjS0aG3/XQFAJnnbACUpFtvvVW33npr0udDoZBisZhisVj2igKAVBDiAGSQs+cAAuni2p4J18aD5Fw7fQFA+hAAgRTZ3lazvf6gSEdoY6oBeCEAAoAPEeIAZBIBEPDgWhONtmBw0O4HkAwBEEiR7ddls7v64GAXMIBsIAACgA8ZUhyADCIAAh6ca6O5Nh4kxVQDSIYACKTI9gUZ2+tH6mw/XQFA5hEAAcCHiHAAMokACHhwbdesW6PBZJw7fQFA2hAAgYCgLWiHUBpSG+1+AF4IgADgQ4Q4AJlEAAQ8uNZGc208SM610xcApA8BEEiR7ddls7z8wCCyAcgGAiAA+BB5HUAmEQABD661TGkLBodr710A6UMABFJkewvV8vIDIz33Ama2AUyOAAgAPkSIA5BJBEDAk1t9NNqCwcFUA0iGAAikyPb1GFaU7BAPbVOZLWYagBcCIAAAQMAQAAEP8ZapKwtotIDdl3ivMtkAkiAAAoCPJO4F7MgvHAD8iQAIeHBtDYXrAAYHMw0gGQIgkCJj+ZKMKy1s16XlOoCWv1cBZB4BEAB8iBAHIJMIgIAH186jd208SI65BpAMARBIke0tVFaU7JCOzGb7exVA5hEAAcCHCHEAMokACHhg1yxsxXsXQDLOBsBYLKZQKDTuEY1GE88bYxSLxVRSUqL8/HwtXbpUnZ2dOawYfmf7ggwrSpZIw4l7TDUAL84GQEmaN2+eDh8+nHjs378/8VxDQ4MaGxvV3Nysjo4ORaNRVVVVaWhoKIcVA8AJBHYAmeR0AMzLy1M0Gk08LrzwQkknVv+ampq0YcMGrVy5UhUVFdq2bZuOHj2q7du357hq+I1rOylDrg0ISTHVAJJxOgC+8847KikpUVlZme644w4dPHhQktTV1aXe3l5VV1cnXhsOh7VkyRK1t7fnqlz4neVLMpaXHxjsAgaQDXm5LiBTFi1apCeffFKXX365fvnLX+rrX/+6Kisr1dnZqd7eXklSJBIZ9z2RSETd3d1Jf+bw8LCGh4cTXw8ODmameACBx2V7AGSSswFw2bJlif++6qqrtHjxYl122WXatm2brrvuOkkTW2HGmEnbY/X19dq4cWNmCoZvudZFc208SI65BpCM0y3gk5199tm66qqr9M477yR2A8dXAuP6+vomrAqerLa2VgMDA4lHT09PRmuGv9i+HmN7/UGRnvP2mG0AkwtMABweHtabb76p2bNnq6ysTNFoVK2trYnnR0ZG1NbWpsrKyqQ/IxwOq6ioaNwDADKB8/gAZJKzLeA///M/14oVK3TRRRepr69PX//61zU4OKjVq1crFAqppqZGdXV1Ki8vV3l5uerq6lRQUKBVq1blunT4jGu7Zh0bDibBXANIxtkA+F//9V+688479f777+vCCy/Uddddp127duniiy+WJK1fv17Hjh3TmjVr1N/fr0WLFqmlpUWFhYU5rhx+ZfuKjLF9AAGRjrt3MNUAvDgbAHfs2DHp86FQSLFYTLFYLDsFAcAZIMMByKTAnAMI4AS6gsHh2ukLANKHAAikyPbrstldfXCkI7PRAgbghQAIAD5EiAOQSQRAwINrXTTaggAAAiCQIutXZGyvPyDSci9gJhuABwIgAPgSIQ5A5hAAAQ/x67LZ/nEcXxWiAey++Go13X4AyRAAAcBHCG0AsoEACHhw7QPZtfG4Kh3nnKbjriIA3EQABFJk+yYQ2+tH6phqAF4IgADgI6zaAcgGAiDgwb2PY/dG5KJ0rOLR7geQDAEQSJHt11azu3qcCdr9ALwQAAHAT367amdIcQAyiAAIeHCtjebaeJAcUw0gGQIgkCrLF2RYULIDt4IDkA0EQADwISIcgEwiAAIeQo71TN0aDSbj2FsXQBoRAIEU2b4iQ1vQDmn5hYOpBuCBAAgAPsQ5mwAyiQAIeHCti0ZbMDi4qwiAZAiAQIpsvy6b5eUHRnp2AQPA5AiAAOBDhDgAmUQABLw41kWjLRgctPsBJEMABFJkewvV8vIDIy2bgG1/swLIOAIgAPgQIQ5AJhEAAQ+utUxpCwIACIBAiqxfj2FFyQpcBxpANhAAAQAAAoYACHiIr8jYvoAWL58WsPvi71XX7mMNIH0IgADgI66dcwrAnwIRAOvr6xUKhVRTU5M4ZoxRLBZTSUmJ8vPztXTpUnV2duauSAA4ie0rzgD8zfkA2NHRoc2bN+vqq68ed7yhoUGNjY1qbm5WR0eHotGoqqqqNDQ0lKNK4Vfx9Rhj+an1ibYgK0zOS7T7c1oFAD9zOgD++te/1l133aUtW7bo3HPPTRw3xqipqUkbNmzQypUrVVFRoW3btuno0aPavn17DisGEHSctgcgG5wOgGvXrtXy5cv12c9+dtzxrq4u9fb2qrq6OnEsHA5ryZIlam9vT/rzhoeHNTg4OO4B9zn3gezaeByVjhVn5967ANImL9cFZMqOHTu0Z88e7d69e8Jzvb29kqRIJDLueCQSUXd3d9KfWV9fr40bN6a3UFjD9nOyuLNEcDDXALw4uQLY09Ojhx56SN///vd11llnJX3dqZdIMMZMetmE2tpaDQwMJB49PT1pqxkAACBbnFwB3LNnj/r6+rRgwYLEsdHRUe3cuVPNzc166623JJ1YCZw9e3biNX19fRNWBU8WDocVDoczVzh8ybVNE26Nxl3pWMRjrgEk4+QK4M0336z9+/dr3759icfChQt11113ad++fbr00ksVjUbV2tqa+J6RkRG1tbWpsrIyh5UDmUNTMDiYawBenFwBLCwsVEVFxbhjZ599ts4///zE8ZqaGtXV1am8vFzl5eWqq6tTQUGBVq1alYuSAUASd+8AkB1OBsBUrF+/XseOHdOaNWvU39+vRYsWqaWlRYWFhbkuDT7j2ucxAcMOaWkBM9cAkghMAHz11VfHfR0KhRSLxRSLxXJSD+xj+85Ky8vHmWCuAXhw8hxAALAVa3YAsoEACHhw7QPZtfG4igtBA8gkAiCQItu7arbXj9TZft9qAJlHAAQAH4mv2nHOJoBMIgACXhzrozk2HEyCqQaQDAEQSJHtKzK272JG6phqAF4IgADgI/FbD5LhAGQSARDw4FobzbXxYBL0+wEkQQAEUsTOSmRDOjIbLWAAXgiAAOBHhDgAGUQABDy41kXj/rDBwUwDSIYACKTI9raa7fUHRTpCG6crAPBCAAQAHyLEAcgkAiDgwZXLcsQDBW1B98VXe+n2A0iGAAgAPkJoA5ANBEAA8CHO2QSQSQRAwEN8Rcb2D+RE/awwOe93U81kAzg9AiAA+AqhDUDmEQABD659HLMqZId0LDhzPiGAZAiAQMrs7gHbXT3OhO2nKwDIPAIgAPgIq3YAsoEACHhw7QPZtfG4yqRhGY+pBpAMARBIke1tNdvrx5lgsgFMjgAIAD7Cqh2AbCAAAh5CjvVM3RqNu9gFDCCTCIBAimxvoRragoFh+3sVQOYRAAHAR1xbcQbgTwRAIGDIF3ZIxyoeF/0GkAwBEEiR7S1U2oLBwVQD8EIABAAfYc0OQDY4GwA3bdqkq6++WkVFRSoqKtLixYv1wgsvJJ43xigWi6mkpET5+flaunSpOjs7c1gx/Mq1liltQTukZRWPqQaQhLMBcM6cOXr88ce1e/du7d69W5/5zGd02223JUJeQ0ODGhsb1dzcrI6ODkWjUVVVVWloaCjHlcOvaKHCFum4iwgAtzkbAFesWKFbbrlFl19+uS6//HI99thjOuecc7Rr1y4ZY9TU1KQNGzZo5cqVqqio0LZt23T06FFt374916UDCDDXVpwB+JOzAfBko6Oj2rFjh44cOaLFixerq6tLvb29qq6uTrwmHA5ryZIlam9vz2Gl8CPXWqYEDEtwL2AAGZSX6wIyaf/+/Vq8eLE+/PBDnXPOOXr22Wc1d+7cRMiLRCLjXh+JRNTd3Z305w0PD2t4eDjx9eDgYGYKhy/Z3lSjLRgczDQAL06vAH7iE5/Qvn37tGvXLj3wwANavXq1Dhw4kHj+1AuuGmMmvQhrfX29iouLE4/S0tKM1Q4gmFihBZANTgfAmTNn6uMf/7gWLlyo+vp6zZ8/X9/+9rcVjUYlSb29veNe39fXN2FV8GS1tbUaGBhIPHp6ejJaP/zBtQ9k18bjqvTcC5jJBnB6TgfAUxljNDw8rLKyMkWjUbW2tiaeGxkZUVtbmyorK5N+fzgcTlxWJv5AcNjeQbW9fqSOuQbgxdlzAL/61a9q2bJlKi0t1dDQkHbs2KFXX31VL774okKhkGpqalRXV6fy8nKVl5errq5OBQUFWrVqVa5LBxBg8U1HhDgAmeRsAPzlL3+pL3zhCzp8+LCKi4t19dVX68UXX1RVVZUkaf369Tp27JjWrFmj/v5+LVq0SC0tLSosLMxx5fCbeBPN+lvBJf6LtqDr4nPNTANIxtkA+MQTT0z6fCgUUiwWUywWy05BAJAKUhuALAjUOYAAYAvbV5wB+BsBEPAQ+l0P2Grxc8rYGOq++DUfmWsAyRAAAcBHyGwAsoEACHhw7lZwuS4AKUnHLmBWAAEkQwAEUmR5B5hzygAACQRAAPAR7t4BIBsIgIAH1z6PXRuPq9LSAqbhDyAJAiCQImP5rRksLx9ngLkG4IUACAA+wpodgGwgAAIBQ1vQDulYxKPdDyAZAiCQItu7arbXj9Sx4xuAFwIgAPgIq3YAsoEACHhw7bIcjg3HWbZvOgLgbwRAIEXWfx5bPwCkiqkG4IUACAA+wiYdANlAAAQ8uPZx7Np4kJxrpy8ASB8CIJAi27tqtteP1NECBuCFAAgAPsKiHYBsIAACHlz7QKYtaIf03AsYAE6PAAikyPbLclhePs4AF4IG4IUACAA+wqodgGwgAAIe+EBGLqRjFY9uP4BkCIBAimxvqtEWDA7a/QC8EAABwE9YtQOQBQRAwENi16zlqyrxVSHagnaYyipe/Fu5qwiAZAiAAAAAAUMABDy4tmLGqpC/pXN+XHvvAkgfAiCQIts3UdhdffBMab6YbAAeCIAAAAABQwAEPLjWRaMt6G+JPUdpuJYLUw0gGQIgkCLbr61me/1Ine2nKwDIPGcDYH19va699loVFhZq1qxZ+tznPqe33npr3GuMMYrFYiopKVF+fr6WLl2qzs7OHFUMAACQHc4GwLa2Nq1du1a7du1Sa2urjh8/rurqah05ciTxmoaGBjU2Nqq5uVkdHR2KRqOqqqrS0NBQDiuH7zjWM3VrNO6Jz0861vAce+sCSKO8XBeQKS+++OK4r7du3apZs2Zpz549uummm2SMUVNTkzZs2KCVK1dKkrZt26ZIJKLt27frvvvuy0XZ8DHbW6i0BYPD9vcqgMxzdgXwVAMDA5Kk8847T5LU1dWl3t5eVVdXJ14TDoe1ZMkStbe3n/ZnDA8Pa3BwcNwDANIpxLIdgCwIRAA0xujhhx/WDTfcoIqKCklSb2+vJCkSiYx7bSQSSTx3qvr6ehUXFycepaWlmS0cvuDaxzH5whJpWcVjsgGcXiAC4Lp16/TGG2/oBz/4wYTnTv1t2xiT9Dfw2tpaDQwMJB49PT0ZqRf+ZH0L1fLykTqmGoAXZ88BjPvSl76k559/Xjt37tScOXMSx6PRqKQTK4GzZ89OHO/r65uwKhgXDocVDoczWzCAQGOFFkA2OLsCaIzRunXr9Mwzz+jHP/6xysrKxj1fVlamaDSq1tbWxLGRkRG1tbWpsrIy2+XCx1z7QOYcMzuwCxhAJjm7Arh27Vpt375d//zP/6zCwsLEeX3FxcXKz89XKBRSTU2N6urqVF5ervLyctXV1amgoECrVq3KcfXwI9t3VlpePs5AOu4iAsBtzgbATZs2SZKWLl067vjWrVt1zz33SJLWr1+vY8eOac2aNerv79eiRYvU0tKiwsLCLFcLACewaAcgG5wNgKn8BhwKhRSLxRSLxTJfEKwVcuwj2a3RuIt7AQPIJGfPAQTSzfamGm3B4GCmAXghAAKAj7BxA0A2EAABD859ILs2HkelZxcwkw3g9AiAQIps76DaXj9Sx1wD8EIABABfYdUOQOYRAAEPrn0cu7ar2VXpWMVjpgEkQwAEUmZ3X83u6nEmmGsAXgiAAOAj7NsAkA0EQMBD/APZ9hPr4/UTMOxgprKO99vJZq4BJEMABAAACBgCIODBtU0Tbo3GPemcH1YAASRDAARSZHkHeGotRWTdVE45YKYBeCEAAgAABAwBEPDiWBuNtqC/pfP2ba6dvgAgfQiAQIqM5duALS8/cKbUAmauAXggAAIAAAQMARDw4FoTjbagv6V1dphqAEkQAIEU0VWDLdjxDcALARAAACBgCICAh3TuyvQDx4bjnHTOD1MNIBkCIJAi23dW2r6LOWimMl9MNQAvBEAAAICAIQACHlxro7k2HtfEd2mnYxHPtdMXAKQPARBIke1dNdvrR+poAQPwQgAEAB9h0Q5ANhAAAQ/OfSA7NyA3pWMVj5kGkAwBEEiR7btoLS8fZ4CpBuCFAAgAABAwBEDAg2sdU8eG46x03M7NtfcugPQhAAIBwf1hg8P20xUAZJ6zAXDnzp1asWKFSkpKFAqF9Nxzz4173hijWCymkpIS5efna+nSpers7MxNsQDwW6zaAcgGZwPgkSNHNH/+fDU3N5/2+YaGBjU2Nqq5uVkdHR2KRqOqqqrS0NBQliuF34Uca5oSMOyQnl3ATDaA08vLdQGZsmzZMi1btuy0zxlj1NTUpA0bNmjlypWSpG3btikSiWj79u267777slkqLGF7V832+gEA6ePsCuBkurq61Nvbq+rq6sSxcDisJUuWqL29PYeVAQg6Vu0AZIOzK4CT6e3tlSRFIpFxxyORiLq7u5N+3/DwsIaHhxNfDw4OZqZA+Eq8ZWr7Jop49QQMO0zl3RZf7aXdDyCZQK4Axp16o3RjzKQ3T6+vr1dxcXHiUVpamukSAQAA0i6QATAajUr63UpgXF9f34RVwZPV1tZqYGAg8ejp6clonUAmsCrkb+mcH6YaQDKBDIBlZWWKRqNqbW1NHBsZGVFbW5sqKyuTfl84HFZRUdG4B4LD9k0UttcfNFOZL9tPVwCQec6eA/jrX/9aP//5zxNfd3V1ad++fTrvvPN00UUXqaamRnV1dSovL1d5ebnq6upUUFCgVatW5bBqAACAzHM2AO7evVuf/vSnE18//PDDkqTVq1frH//xH7V+/XodO3ZMa9asUX9/vxYtWqSWlhYVFhbmqmT41GTnhdrIrdG4J61vNyYbQBLOBsClS5dOejukUCikWCymWCyWvaJgNftbqNYPIGA++nzZ/14FkGmBPAcQAAAgyAiAgAfXumiOdbSdk87rNHLNRwDJEACBFNm+s5K2oF2mtgsYACZHAAQAAAgYAiDgwbWWqWu7ml2T1gtBM9UAkiAAAimyvYVqe/1BM7V7ATPZACZHAAQAAAgYAiDggZ2UyCauAw0gGwiAQIpsb6rZvos5aKbSxmWmAXghAAIAAAQMARDw4NpOStfG45r07gJmsgGcHgEQSJXlfTU2htplStPFXAPwQAAEAAAIGAIg4MG1Jhq7mv3uxPykY8WWDjCAZAiAQIps30Vrd/U4E8w1AC8EQAAAgIAhAAIeXGujuTYe18TnJx23c2OqASRDAARSZPsuWtvrR+q4FzAALwRAAPARVu0AZAMBEPD0212ZOa5iquKbWAgYdpjK+y3+vbT7ASRDAAQAAAgYAiDgwbVVFNfG45r03r6NyQZwegRAIEXWn1hvefmBM4X5sv2tCiDzCIAAAAABQwAEPLjWRONWcP6W1gYwUw0gCQIgkCLbu2q21x80U9sFzGwDmBwBEAAAIGAIgICH9O7KzD3HhuOcdM4PUw0gGQIgkCLbd1Zav4s5YKYyX0w1AC8EQAAAgIDJy3UBgN+NHh+TJL357gf61Nde1OiYND0khfOmSzIaPj6mUXPi2Mzp0zQy+ruvT/eabH9f/DVDw6OSpH//+f/T3Ysv0cw8fv/zo98cP7F8d2RkVJX1rTJjZz7nHxw7MdfP7X1X80qKmWsAE4RMwPtC3/3ud/XNb35Thw8f1rx589TU1KQbb7wxpe8dHBxUcXGxBgYGVFRUlOFKkQv1Pzqgv9/ZlesyMuK+m8pUe8vcXJeBk2Ti/RaS9KfMNTAOn98BbwE//fTTqqmp0YYNG7R3717deOONWrZsmQ4dOpTr0uADLoc/Sfr7nV2q/9GBXJeB38rU+82IuQYwUaADYGNjo/74j/9YX/ziF3XllVeqqalJpaWl2rRpU65LQ46NHB9zOvzFbflJl0Z+2+JG7mTj/cZcAzhZYAPgyMiI9uzZo+rq6nHHq6ur1d7eftrvGR4e1uDg4LgH3PRPr/8i1yVkxZgJzlj9LBtzwFwDOFlgA+D777+v0dFRRSKRcccjkYh6e3tP+z319fUqLi5OPEpLS7NRKnKg+7+P5rqErAnSWP0qW3PAXAOIC2wAjDv1Ir/GmKQX/q2trdXAwEDi0dPTk40SkQMXn1eQ6xKyJkhj9atszQFzDSAusAHwggsu0PTp0yes9vX19U1YFYwLh8MqKioa94CbvrD4klyXkBXTQsEZq59lYw6YawAnC2wAnDlzphYsWKDW1tZxx1tbW1VZWZmjquAXM/Om6b6bynJdRsb9yY1lXCPOB7LxfmOuAZws0BeCfvjhh/WFL3xBCxcu1OLFi7V582YdOnRI999/f65Lgw/Er5vm6m5grgPoL5l6v3EdQACnw4Wgv/tdNTQ06PDhw6qoqNDf/M3f6Kabbkrpe7mQZDCMHB/T1n8/qBf3H1b3fx+x9k4gJjRNF54zUys/NUf33nApq0E+FX+/vfSzXvUOHvtIdwLJnzlD0eKz9Pvzorrnelb+gFPx+U0AnBLeQAAA2IfP7wCfAwgAABBUBEAAAICAIQACAAAEDAEQAAAgYAiAAAAAAUMABAAACBgCIAAAQMAQAAEAAAKGAAgAABAwgb4X8FTFb6IyODiY40oAAECq4p/bQb4ZGgFwCoaGhiRJpaWlOa4EAACcqaGhIRUXF+e6jJzgXsBTMDY2pvfee0+FhYUKhUIf6WcMDg6qtLRUPT09Tt6P0OXxuTw2ifHZzOWxSYzPZn4ZmzFGQ0NDKikp0bRpwTwbjhXAKZg2bZrmzJmTlp9VVFTk3F/0k7k8PpfHJjE+m7k8Nonx2cwPYwvqyl9cMGMvAABAgBEAAQAAAoYAmGPhcFiPPvqowuFwrkvJCJfH5/LYJMZnM5fHJjE+m7k8NtuwCQQAACBgWAEEAAAIGAIgAABAwBAAAQAAAoYACAAAEDAEwBx67LHHVFlZqYKCAn3sYx877WsOHTqkFStW6Oyzz9YFF1ygBx98UCMjI9kt9CP67ne/q7KyMp111llasGCBfvKTn+S6pI9k586dWrFihUpKShQKhfTcc8+Ne94Yo1gsppKSEuXn52vp0qXq7OzMTbFnqL6+Xtdee60KCws1a9Ysfe5zn9Nbb7017jU2j2/Tpk26+uqrExedXbx4sV544YXE8zaP7VT19fUKhUKqqalJHLN5fLFYTKFQaNwjGo0mnrd5bHHvvvuuPv/5z+v8889XQUGBPvnJT2rPnj2J520e4yWXXDJh/kKhkNauXSvJ7rG5ggCYQyMjI7r99tv1wAMPnPb50dFRLV++XEeOHNFrr72mHTt26Ic//KG+/OUvZ7nSM/f000+rpqZGGzZs0N69e3XjjTdq2bJlOnToUK5LO2NHjhzR/Pnz1dzcfNrnGxoa1NjYqObmZnV0dCgajaqqqipxr2g/a2tr09q1a7Vr1y61trbq+PHjqq6u1pEjRxKvsXl8c+bM0eOPP67du3dr9+7d+sxnPqPbbrst8UFj89hO1tHRoc2bN+vqq68ed9z28c2bN0+HDx9OPPbv3594zvax9ff36/rrr9eMGTP0wgsv6MCBA/rWt741bjHA5jF2dHSMm7vW1lZJ0u233y7J7rE5wyDntm7daoqLiycc/9GPfmSmTZtm3n333cSxH/zgByYcDpuBgYEsVnjmfu/3fs/cf//9445dccUV5itf+UqOKkoPSebZZ59NfD02Nmai0ah5/PHHE8c+/PBDU1xcbL73ve/loMKp6evrM5JMW1ubMca98RljzLnnnmv+4R/+wZmxDQ0NmfLyctPa2mqWLFliHnroIWOM/XP36KOPmvnz55/2OdvHZowxjzzyiLnhhhuSPu/CGE/20EMPmcsuu8yMjY05NzZbsQLoY6+//roqKipUUlKSOPb7v//7Gh4eHtcm8JuRkRHt2bNH1dXV445XV1ervb09R1VlRldXl3p7e8eNNRwOa8mSJVaOdWBgQJJ03nnnSXJrfKOjo9qxY4eOHDmixYsXOzO2tWvXavny5frsZz877rgL43vnnXdUUlKisrIy3XHHHTp48KAkN8b2/PPPa+HChbr99ts1a9YsXXPNNdqyZUvieRfGGDcyMqKnnnpK9957r0KhkFNjsxkB0Md6e3sViUTGHTv33HM1c+ZM9fb25qgqb++//75GR0cn1B6JRHxd90cRH48LYzXG6OGHH9YNN9ygiooKSW6Mb//+/TrnnHMUDod1//3369lnn9XcuXOdGNuOHTu0Z88e1dfXT3jO9vEtWrRITz75pF566SVt2bJFvb29qqys1K9+9SvrxyZJBw8e1KZNm1ReXq6XXnpJ999/vx588EE9+eSTkuyfv5M999xz+uCDD3TPPfdIcmtsNsvLdQGuicVi2rhx46Sv6ejo0MKFC1P6eaFQaMIxY8xpj/vNqTXaUvdH4cJY161bpzfeeEOvvfbahOdsHt8nPvEJ7du3Tx988IF++MMfavXq1Wpra0s8b+vYenp69NBDD6mlpUVnnXVW0tfZOr5ly5Yl/vuqq67S4sWLddlll2nbtm267rrrJNk7NkkaGxvTwoULVVdXJ0m65ppr1NnZqU2bNunuu+9OvM7mMcY98cQTWrZs2bhuluTG2GzGCmCarVu3Tm+++eakj/jqipdoNDrht6H+/n795je/mfCbk59ccMEFmj59+oTa+/r6fF33RxHflWj7WL/0pS/p+eef1yuvvKI5c+YkjrswvpkzZ+rjH/+4Fi5cqPr6es2fP1/f/va3rR/bnj171NfXpwULFigvL095eXlqa2vT3/7t3yovLy8xBlvHd6qzzz5bV111ld555x3r506SZs+erblz5447duWVVyY2yrkwRknq7u7Wyy+/rC9+8YuJY66MzXYEwDS74IILdMUVV0z6mOy39ZMtXrxYP/vZz3T48OHEsZaWFoXDYS1YsCBTQ5iymTNnasGCBYldX3Gtra2qrKzMUVWZUVZWpmg0Om6sIyMjamtrs2KsxhitW7dOzzzzjH784x+rrKxs3PO2j+90jDEaHh62fmw333yz9u/fr3379iUeCxcu1F133aV9+/bp0ksvtXp8pxoeHtabb76p2bNnWz93knT99ddPuOTS22+/rYsvvliSO3/3tm7dqlmzZmn58uWJY66MzXq52XsCY4zp7u42e/fuNRs3bjTnnHOO2bt3r9m7d68ZGhoyxhhz/PhxU1FRYW6++WbzH//xH+bll182c+bMMevWrctx5d527NhhZsyYYZ544glz4MABU1NTY84++2zzi1/8ItelnbGhoaHE3EgyjY2NZu/evaa7u9sYY8zjjz9uiouLzTPPPGP2799v7rzzTjN79mwzODiY48q9PfDAA6a4uNi8+uqr5vDhw4nH0aNHE6+xeXy1tbVm586dpqury7zxxhvmq1/9qpk2bZppaWkxxtg9ttM5eRewMXaP78tf/rJ59dVXzcGDB82uXbvMrbfeagoLCxP/htg8NmOM+elPf2ry8vLMY489Zt555x3z/e9/3xQUFJinnnoq8Rrbxzg6Omouuugi88gjj0x4zvaxuYAAmEOrV682kiY8XnnllcRruru7zfLly01+fr4577zzzLp168yHH36Yu6LPwN/93d+Ziy++2MycOdN86lOfSlxaxDavvPLKaedp9erVxpgTl2t49NFHTTQaNeFw2Nx0001m//79uS06RacblySzdevWxGtsHt+9996beA9eeOGF5uabb06EP2PsHtvpnBoAbR7fH/3RH5nZs2ebGTNmmJKSErNy5UrT2dmZeN7mscX9y7/8i6moqDDhcNhcccUVZvPmzeOet32ML730kpFk3nrrrQnP2T42F4SMMSbbq44AAADIHc4BBAAACBgCIAAAQMAQAAEAAAKGAAgAABAwBEAAAICAIQACAAAEDAEQAAAgYAiAAAAAAUMABAAACBgCIAAAQMAQAAEAAAKGAAgAABAwBEAAAICAIQACAAAEDAEQAAAgYAiAAAAAAUMABAAACBgCIAAAQMAQAAEAAAKGAAgAABAwBEAAAICAIQACAAAEDAEQAAAgYAiAAAAAAUMABAAACBgCIAAAQMAQAAEAAAKGAAgAABAwBEAAAICAIQACAAAEDAEQAAAgYP4/3ITkDHhkeF8AAAAASUVORK5CYII=' width=640.0/>\n",
|
|
" </div>\n",
|
|
" "
|
|
],
|
|
"text/plain": [
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"sample_time = np.linspace(-9, 72, 1000)\n",
|
|
"plt.figure()\n",
|
|
"plt.plot(sample_time, np.interp(sample_time, sample_charging.xp, sample_charging.fp), '-o')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "d5717ba9",
|
|
"metadata": {},
|
|
"source": [
|
|
"# Battery Simulation"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "d24575f8",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 배터리 객체 초기화"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 20,
|
|
"id": "235b5f6e",
|
|
"metadata": {
|
|
"scrolled": false
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Push timing within [ -58.39730639730638 , -58.37037037037035 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -58.101010101010075 , -58.07407407407405 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -57.80471380471377 , -57.77777777777774 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -57.508417508417466 , -57.48148148148144 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -57.21212121212116 , -57.185185185185134 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -56.91582491582486 , -56.88888888888883 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -56.61952861952855 , -56.592592592592524 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -56.32323232323225 , -56.29629629629622 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -56.02693602693594 , -55.999999999999915 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -55.73063973063964 , -55.70370370370361 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -55.43434343434333 , -55.407407407407305 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -55.13804713804703 , -55.111111111111 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -54.841750841750724 , -54.814814814814696 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -54.54545454545442 , -54.51851851851839 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -54.249158249158114 , -54.222222222222086 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -53.95286195286181 , -53.92592592592578 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -53.656565656565505 , -53.62962962962948 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -53.3602693602692 , -53.33333333333317 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -53.063973063972895 , -53.03703703703687 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -52.76767676767659 , -52.74074074074056 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -52.471380471380286 , -52.44444444444426 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -52.17508417508398 , -52.14814814814795 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -51.878787878787676 , -51.85185185185165 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -51.58249158249137 , -51.555555555555344 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -51.28619528619507 , -51.25925925925904 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -50.98989898989876 , -50.962962962962735 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -50.69360269360246 , -50.66666666666643 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -50.39730639730615 , -50.370370370370125 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -50.10101010100985 , -50.07407407407382 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -49.80471380471354 , -49.777777777777516 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -49.50841750841724 , -49.48148148148121 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -49.212121212120934 , -49.185185185184906 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -48.91582491582463 , -48.8888888888886 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -48.619528619528324 , -48.5925925925923 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -48.32323232323202 , -48.29629629629599 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -48.026936026935715 , -47.99999999999969 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -47.73063973063941 , -47.70370370370338 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -47.434343434343106 , -47.40740740740708 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -47.1380471380468 , -47.11111111111077 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -46.841750841750496 , -46.81481481481447 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -46.54545454545419 , -46.518518518518164 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -46.24915824915789 , -46.22222222222186 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -45.95286195286158 , -45.925925925925554 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -45.65656565656528 , -45.62962962962925 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -45.36026936026897 , -45.333333333332945 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -45.06397306397267 , -45.03703703703664 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -44.76767676767636 , -44.740740740740335 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -44.47138047138006 , -44.44444444444403 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -44.175084175083754 , -44.148148148147726 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -43.87878787878745 , -43.85185185185142 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -43.582491582491144 , -43.55555555555512 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -43.28619528619484 , -43.25925925925881 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -42.989898989898535 , -42.96296296296251 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -42.69360269360223 , -42.6666666666662 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -42.397306397305925 , -42.3703703703699 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -42.10101010100962 , -42.07407407407359 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -41.804713804713316 , -41.77777777777729 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -41.50841750841701 , -41.481481481480984 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -41.21212121212071 , -41.18518518518468 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -40.9158249158244 , -40.888888888888374 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -40.6195286195281 , -40.59259259259207 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -40.32323232323179 , -40.296296296295765 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -40.02693602693549 , -39.99999999999946 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -39.73063973063918 , -39.703703703703155 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -39.43434343434288 , -39.40740740740685 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -39.13804713804657 , -39.111111111110546 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -38.84175084175027 , -38.81481481481424 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -38.545454545453964 , -38.518518518517936 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -38.24915824915766 , -38.22222222222163 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -37.952861952861355 , -37.92592592592533 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -37.65656565656505 , -37.62962962962902 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -37.360269360268745 , -37.33333333333272 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -37.06397306397244 , -37.03703703703641 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -36.767676767676136 , -36.74074074074011 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -36.47138047137983 , -36.4444444444438 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -36.175084175083526 , -36.1481481481475 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -35.87878787878722 , -35.851851851851194 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -35.58249158249092 , -35.55555555555489 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -35.28619528619461 , -35.259259259258585 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -34.98989898989831 , -34.96296296296228 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -34.693602693602 , -34.666666666665975 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -34.3973063973057 , -34.37037037036967 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -34.10101010100939 , -34.074074074073366 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -33.80471380471309 , -33.77777777777706 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -33.508417508416784 , -33.481481481480756 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -33.21212121212048 , -33.18518518518445 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -32.915824915824174 , -32.88888888888815 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -32.61952861952787 , -32.59259259259184 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -32.323232323231565 , -32.29629629629554 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -32.02693602693526 , -31.999999999999233 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -31.730639730638956 , -31.703703703702928 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -31.43434343434265 , -31.407407407406623 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -31.138047138046346 , -31.11111111111032 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -30.84175084175004 , -30.814814814814014 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -30.545454545453737 , -30.51851851851771 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -30.249158249157432 , -30.222222222221404 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -29.952861952861127 , -29.9259259259251 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -29.656565656564823 , -29.629629629628795 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -29.360269360268518 , -29.33333333333249 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -29.063973063972213 , -29.037037037036185 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -28.76767676767591 , -28.74074074073988 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -28.471380471379604 , -28.444444444443576 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -28.1750841750833 , -28.14814814814727 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -27.878787878786994 , -27.851851851850967 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -27.58249158249069 , -27.555555555554662 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -27.286195286194385 , -27.259259259258357 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -26.98989898989808 , -26.962962962962052 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -26.693602693601775 , -26.666666666665748 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -26.39730639730547 , -26.370370370369443 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -26.101010101009166 , -26.07407407407314 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -25.80471380471286 , -25.777777777776834 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -25.508417508416557 , -25.48148148148053 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -25.212121212120252 , -25.185185185184224 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -24.915824915823947 , -24.88888888888792 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -24.619528619527642 , -24.592592592591615 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -24.323232323231338 , -24.29629629629531 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -24.026936026935033 , -23.999999999999005 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -23.73063973063873 , -23.7037037037027 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -23.434343434342424 , -23.407407407406396 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -23.13804713804612 , -23.11111111111009 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -22.841750841749814 , -22.814814814813786 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -22.54545454545351 , -22.51851851851748 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -22.249158249157205 , -22.222222222221177 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -21.9528619528609 , -21.925925925924872 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -21.656565656564595 , -21.629629629628567 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -21.36026936026829 , -21.333333333332263 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -21.063973063971986 , -21.037037037035958 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -20.76767676767568 , -20.740740740739653 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -20.471380471379376 , -20.44444444444335 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -20.17508417508307 , -20.148148148147044 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -19.878787878786767 , -19.85185185185074 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -19.582491582490462 , -19.555555555554434 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -19.286195286194157 , -19.25925925925813 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -18.989898989897853 , -18.962962962961825 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -18.693602693601548 , -18.66666666666552 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -18.397306397305243 , -18.370370370369216 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -18.10101010100894 , -18.07407407407291 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -17.804713804712634 , -17.777777777776606 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -17.50841750841633 , -17.4814814814803 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -17.212121212120024 , -17.185185185183997 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -16.91582491582372 , -16.888888888887692 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -16.619528619527415 , -16.592592592591387 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -16.32323232323111 , -16.296296296295083 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -16.026936026934806 , -15.999999999998778 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -15.7306397306385 , -15.703703703702473 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -15.434343434342196 , -15.407407407406168 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -15.138047138045891 , -15.111111111109864 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -14.841750841749587 , -14.814814814813559 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -14.545454545453282 , -14.518518518517254 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -14.249158249156977 , -14.22222222222095 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -13.952861952860673 , -13.925925925924645 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -13.656565656564368 , -13.62962962962834 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -13.360269360268063 , -13.333333333332035 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -13.063973063971758 , -13.03703703703573 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -12.767676767675454 , -12.740740740739426 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -12.471380471379149 , -12.444444444443121 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -12.175084175082844 , -12.148148148146817 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -11.87878787878654 , -11.851851851850512 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -11.582491582490235 , -11.555555555554207 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -11.28619528619393 , -11.259259259257902 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -10.989898989897625 , -10.962962962961598 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -10.69360269360132 , -10.666666666665293 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -10.397306397305016 , -10.370370370368988 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -10.101010101008711 , -10.074074074072684 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -9.804713804712406 , -9.777777777776379 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -9.508417508416102 , -9.481481481480074 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -9.212121212119797 , -9.18518518518377 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -8.915824915823492 , -8.888888888887465 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -8.619528619527188 , -8.59259259259116 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -8.323232323230883 , -8.296296296294855 ]. 0.2962962962963047 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -8.026936026934578 , -7.999999999998551 ]. 0.29629629629630383 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -7.730639730638283 , -7.703703703702256 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -7.434343434341988 , -7.4074074074059615 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -7.138047138045693 , -7.1111111111096665 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -6.841750841749398 , -6.814814814813372 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -6.5454545454531035 , -6.518518518517077 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -6.2491582491568085 , -6.222222222220782 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -5.952861952860514 , -5.925925925924487 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -5.656565656564219 , -5.629629629628192 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -5.360269360267924 , -5.333333333331897 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -5.063973063971629 , -5.037037037035602 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -4.767676767675334 , -4.740740740739307 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -4.471380471379039 , -4.444444444443012 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -4.175084175082744 , -4.148148148146717 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -3.878787878786449 , -3.851851851850422 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -3.582491582490154 , -3.555555555554127 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -3.286195286193859 , -3.259259259257832 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -2.989898989897564 , -2.9629629629615373 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -2.693602693601269 , -2.6666666666652423 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -2.397306397304974 , -2.3703703703689474 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -2.1010101010086792 , -2.0740740740726524 ]. 0.29629629629629495 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -1.8047138047123825 , -1.7777777777763555 ]. 0.29629629629629695 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -1.5084175084160851 , -1.481481481480058 ]. 0.2962962962962974 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -1.2121212121197877 , -1.1851851851837607 ]. 0.2962962962962974 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -0.9158249158234908 , -0.8888888888874639 ]. 0.29629629629629683 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -0.6195286195271946 , -0.5925925925911677 ]. 0.29629629629629617 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -0.32323232323089846 , -0.29629629629487153 ]. 0.29629629629629617 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ -0.026936026934602234 , 1.424700635244136e-12 ]. 0.2962962962962962 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"1405.925925925954 -19.25925925925813 0\n",
|
|
"1384.2962962963227 -18.962962962961825 5\n",
|
|
"1362.666666666691 -18.66666666666552 10\n",
|
|
"1341.0370370370597 -18.370370370369216 15\n",
|
|
"1319.407407407428 -18.07407407407291 20\n",
|
|
"1297.7777777777967 -17.777777777776606 25\n",
|
|
"1276.148148148165 -17.4814814814803 30\n",
|
|
"1254.5185185185337 -17.185185185183997 35\n",
|
|
"1232.888888888902 -16.888888888887692 40\n",
|
|
"1211.2592592592707 -16.592592592591387 45\n",
|
|
"1189.629629629639 -16.296296296295083 50\n",
|
|
"1168.0000000000077 -15.999999999998778 55\n",
|
|
"1146.3703703703775 -15.703703703702473 60\n",
|
|
"1124.7407407407472 -15.407407407406168 65\n",
|
|
"1103.111111111117 -15.111111111109864 2\n",
|
|
"1081.4814814814863 -14.814814814813559 7\n",
|
|
"1059.8518518518556 -14.518518518517254 12\n",
|
|
"1038.2222222222247 -14.22222222222095 17\n",
|
|
"1016.5925925925949 -13.925925925924645 22\n",
|
|
"994.9629629629651 -13.62962962962834 27\n",
|
|
"973.3333333333355 -13.333333333332035 32\n",
|
|
"951.703703703706 -13.03703703703573 37\n",
|
|
"930.0740740740764 -12.740740740739426 42\n",
|
|
"908.4444444444466 -12.444444444443121 47\n",
|
|
"886.814814814817 -12.148148148146817 52\n",
|
|
"865.1851851851875 -11.851851851850512 57\n",
|
|
"843.5555555555579 -11.555555555554207 62\n",
|
|
"821.9259259259281 -11.259259259257902 4\n",
|
|
"800.2962962962986 -10.962962962961598 9\n",
|
|
"778.666666666669 -10.666666666665293 14\n",
|
|
"757.0370370370395 -10.370370370368988 19\n",
|
|
"735.4074074074097 -10.074074074072684 24\n",
|
|
"713.7777777777801 -9.777777777776379 29\n",
|
|
"692.1481481481503 -9.481481481480074 34\n",
|
|
"670.5185185185205 -9.18518518518377 39\n",
|
|
"648.88888888889 -8.888888888887465 44\n",
|
|
"627.2592592592591 -8.59259259259116 49\n",
|
|
"605.6296296296282 -8.296296296294855 54\n",
|
|
"583.9999999999975 -7.999999999998551 59\n",
|
|
"562.3703703703685 -7.703703703702256 64\n",
|
|
"540.7407407407395 -7.4074074074059615 1\n",
|
|
"519.1111111111103 -7.1111111111096665 6\n",
|
|
"497.4814814814805 -6.814814814813372 11\n",
|
|
"475.8518518518509 -6.518518518517077 16\n",
|
|
"454.22222222222126 -6.222222222220782 21\n",
|
|
"432.59259259259164 -5.925925925924487 26\n",
|
|
"410.962962962962 -5.629629629628192 31\n",
|
|
"389.33333333333246 -5.333333333331897 36\n",
|
|
"367.70370370370284 -5.037037037035602 41\n",
|
|
"346.0740740740732 -4.740740740739307 46\n",
|
|
"324.44444444444355 -4.444444444443012 51\n",
|
|
"302.81481481481393 -4.148148148146717 56\n",
|
|
"281.1851851851843 -3.851851851850422 61\n",
|
|
"259.555555555555 -3.555555555554127 3\n",
|
|
"237.92592592592567 -3.259259259257832 8\n",
|
|
"216.29629629629636 -2.9629629629615373 13\n",
|
|
"194.66666666666686 -2.6666666666652423 18\n",
|
|
"173.03703703703724 -2.3703703703689474 23\n",
|
|
"151.40740740740762 -2.0740740740726524 28\n",
|
|
"129.77777777777794 -1.7777777777763555 33\n",
|
|
"108.14814814814822 -1.481481481480058 38\n",
|
|
"86.51851851851852 -1.1851851851837607 43\n",
|
|
"64.88888888888886 -0.8888888888874639 48\n",
|
|
"43.25925925925923 -0.5925925925911677 53\n",
|
|
"21.62962962962962 -0.29629629629487153 58\n",
|
|
"0 1.424700635244136e-12 63\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"bat3A = Battery(\"3A\", 66, sample_schedule2, sample_charging, 1220) \n",
|
|
"\n",
|
|
"for cc in bat3A.processing:\n",
|
|
" print (cc.Q, cc.t_charge, cc.idx_oven)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "41951d5c",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 시뮬레이션 실행"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 21,
|
|
"id": "c38bbf3e",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"0.2962962962962963"
|
|
]
|
|
},
|
|
"execution_count": 21,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"bat3A.charge_program.period(6)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 22,
|
|
"id": "99d40063",
|
|
"metadata": {
|
|
"scrolled": true
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Push timing within [ 0.29333333333475775 , 0.3000000000014244 ]. 0.2999999999999997 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 0.5866666666680913 , 0.593333333334758 ]. 0.2933333333333336 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 0.8866666666680932 , 0.89333333333476 ]. 0.30000000000000193 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 1.1800000000014255 , 1.186666666668092 ]. 0.2933333333333321 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 1.4800000000014224 , 1.486666666668089 ]. 0.29999999999999694 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 1.7733333333347527 , 1.7800000000014193 ]. 0.29333333333333034 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 2.073333333334752 , 2.080000000001419 ]. 0.2999999999999996 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 2.3666666666680922 , 2.373333333334759 ]. 0.2933333333333401 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 2.6600000000014323 , 2.666666666668099 ]. 0.2933333333333401 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 2.9600000000014393 , 2.966666666668106 ]. 0.30000000000000693 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 3.2533333333347794 , 3.260000000001446 ]. 0.2933333333333401 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 3.5533333333347863 , 3.560000000001453 ]. 0.30000000000000693 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 3.8466666666681264 , 3.853333333334793 ]. 0.2933333333333401 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 4.146666666668133 , 4.1533333333348 ]. 0.3000000000000065 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 4.440000000001473 , 4.44666666666814 ]. 0.2933333333333401 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 4.74000000000148 , 4.746666666668147 ]. 0.30000000000000693 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 5.03333333333482 , 5.040000000001487 ]. 0.2933333333333401 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 5.32666666666816 , 5.333333333334827 ]. 0.2933333333333401 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 5.626666666668167 , 5.633333333334834 ]. 0.30000000000000693 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 5.920000000001507 , 5.926666666668174 ]. 0.2933333333333401 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 6.220000000001514 , 6.226666666668181 ]. 0.30000000000000693 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 6.513333333334854 , 6.520000000001521 ]. 0.2933333333333401 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 6.813333333334861 , 6.820000000001528 ]. 0.30000000000000693 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 7.106666666668201 , 7.113333333334868 ]. 0.2933333333333401 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 7.406666666668208 , 7.413333333334875 ]. 0.30000000000000693 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 7.700000000001548 , 7.706666666668215 ]. 0.2933333333333401 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 7.993333333334888 , 8.000000000001554 ]. 0.2933333333333392 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 8.293333333334855 , 8.300000000001521 ]. 0.29999999999996696 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 8.586666666668156 , 8.593333333334822 ]. 0.293333333333301 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 8.886666666668123 , 8.89333333333479 ]. 0.29999999999996696 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 18.000000000000988 , 18.006666666667655 ]. 9.113333333332866 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 18.300000000001035 , 18.306666666667702 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 18.593333333334414 , 18.60000000000108 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 18.89333333333446 , 18.90000000000113 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 19.18666666666784 , 19.193333333334508 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 19.486666666667887 , 19.493333333334554 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 19.780000000001266 , 19.786666666667934 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 20.080000000001313 , 20.08666666666798 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 20.373333333334692 , 20.38000000000136 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 20.66666666666807 , 20.67333333333474 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 20.966666666668118 , 20.973333333334786 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 21.260000000001497 , 21.266666666668165 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 21.560000000001544 , 21.566666666668212 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 21.853333333334923 , 21.86000000000159 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 22.15333333333497 , 22.160000000001638 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 22.44666666666835 , 22.453333333335017 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 22.746666666668396 , 22.753333333335064 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 23.040000000001776 , 23.046666666668443 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 23.333333333335155 , 23.340000000001822 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 23.6333333333352 , 23.64000000000187 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 23.92666666666858 , 23.93333333333525 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 24.226666666668628 , 24.233333333335295 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 24.520000000002007 , 24.526666666668675 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 24.820000000002054 , 24.82666666666872 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 25.113333333335433 , 25.1200000000021 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 25.41333333333548 , 25.420000000002148 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 25.70666666666886 , 25.713333333335527 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 26.000000000002238 , 26.006666666668906 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 26.300000000002285 , 26.306666666668953 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 26.593333333335664 , 26.600000000002332 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 26.89333333333571 , 26.90000000000238 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 27.18666666666909 , 27.193333333335758 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 27.486666666669137 , 27.493333333335805 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 27.780000000002516 , 27.786666666669184 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 28.080000000002563 , 28.08666666666923 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 28.373333333335943 , 28.38000000000261 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 28.66666666666932 , 28.67333333333599 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 28.96666666666937 , 28.973333333336036 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 29.260000000002748 , 29.266666666669416 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 29.560000000002795 , 29.566666666669462 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 29.853333333336174 , 29.86000000000284 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 30.15333333333622 , 30.16000000000289 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 30.4466666666696 , 30.453333333336268 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 30.746666666669647 , 30.753333333336315 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 31.040000000003026 , 31.046666666669694 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 31.333333333336405 , 31.340000000003073 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 31.633333333336452 , 31.64000000000312 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 31.92666666666983 , 31.9333333333365 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 32.22666666666988 , 32.233333333336546 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 32.52000000000326 , 32.526666666669925 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 32.820000000003304 , 32.82666666666997 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 33.11333333333668 , 33.12000000000335 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 33.41333333333673 , 33.4200000000034 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 33.70666666667011 , 33.71333333333678 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 34.00000000000349 , 34.00666666667016 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 34.300000000003536 , 34.3066666666702 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 34.593333333336915 , 34.60000000000358 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 34.89333333333696 , 34.90000000000363 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 35.18666666667034 , 35.19333333333701 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 35.48666666667039 , 35.493333333337056 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 35.78000000000377 , 35.786666666670435 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 36.080000000003814 , 36.08666666667048 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 36.37333333333719 , 36.38000000000386 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 36.66666666667057 , 36.67333333333724 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 36.96666666667062 , 36.97333333333729 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 40.00000000000443 , 40.006666666671094 ]. 3.0333333333338075 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 40.300000000004474 , 40.30666666667114 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 40.59333333333785 , 40.60000000000452 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 40.8933333333379 , 40.90000000000457 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 41.18666666667128 , 41.19333333333795 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 41.486666666671326 , 41.49333333333799 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 41.780000000004705 , 41.78666666667137 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 42.08000000000475 , 42.08666666667142 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 42.37333333333813 , 42.3800000000048 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 42.66666666667151 , 42.67333333333818 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 42.96666666667156 , 42.973333333338225 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 43.260000000004936 , 43.266666666671604 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 43.56000000000498 , 43.56666666667165 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 43.85333333333836 , 43.86000000000503 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 44.15333333333841 , 44.16000000000508 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 44.44666666667179 , 44.453333333338456 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 44.746666666671835 , 44.7533333333385 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 45.040000000005215 , 45.04666666667188 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 45.333333333338594 , 45.34000000000526 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 45.63333333333864 , 45.64000000000531 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 45.92666666667202 , 45.93333333333869 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 46.22666666667207 , 46.233333333338734 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 46.520000000005446 , 46.526666666672114 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 46.82000000000549 , 46.82666666667216 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 47.11333333333887 , 47.12000000000554 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 47.41333333333892 , 47.42000000000559 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 47.7066666666723 , 47.713333333338966 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 48.00000000000568 , 48.006666666672345 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 48.300000000005724 , 48.30666666667239 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 48.5933333333391 , 48.60000000000577 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n"
|
|
]
|
|
},
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Push timing within [ 48.89333333333915 , 48.90000000000582 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 49.18666666667253 , 49.1933333333392 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 49.486666666672576 , 49.493333333339244 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 49.780000000005955 , 49.78666666667262 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 50.080000000006 , 50.08666666667267 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 50.37333333333938 , 50.38000000000605 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 50.66666666667276 , 50.67333333333943 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 50.96666666667281 , 50.973333333339475 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 51.26000000000619 , 51.266666666672855 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 51.560000000006234 , 51.5666666666729 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 51.85333333333961 , 51.86000000000628 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 52.15333333333966 , 52.16000000000633 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 52.44666666667304 , 52.45333333333971 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 52.746666666673086 , 52.753333333339754 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 53.040000000006465 , 53.04666666667313 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 53.333333333339844 , 53.34000000000651 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 53.63333333333989 , 53.64000000000656 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 53.92666666667327 , 53.93333333333994 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 54.22666666667332 , 54.233333333339985 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 54.520000000006696 , 54.526666666673364 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 54.82000000000674 , 54.82666666667341 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 55.11333333334012 , 55.12000000000679 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 55.41333333334017 , 55.42000000000684 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 55.70666666667355 , 55.713333333340216 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 56.00000000000693 , 56.006666666673596 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 56.300000000006975 , 56.30666666667364 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 56.593333333340354 , 56.60000000000702 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 56.8933333333404 , 56.90000000000707 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 57.18666666667378 , 57.19333333334045 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 57.48666666667383 , 57.493333333340495 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 57.780000000007206 , 57.786666666673874 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 58.08000000000725 , 58.08666666667392 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 58.37333333334063 , 58.3800000000073 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 58.66666666667401 , 58.67333333334068 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 58.96666666667406 , 58.973333333340726 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 59.26000000000744 , 59.266666666674105 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 59.560000000007484 , 59.56666666667415 ]. 0.3000000000000469 since last P/C. P/C interval = 0.2962962962962963\n",
|
|
"Push timing within [ 59.85333333334086 , 59.86000000000753 ]. 0.2933333333333792 since last P/C. P/C interval = 0.2962962962962963\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"t = 0\n",
|
|
"dt = 1 / 60. / 2.5 # 1 min = 1/60 hour\n",
|
|
"n_steps = int(60/dt)\n",
|
|
"# meanQ = [np.mean([cc.Q for cc in bat3A.processing])]\n",
|
|
"meanQ = []\n",
|
|
"for it in range (int(60/dt)): # 시뮬레이션 시간 도메인 = 60시간\n",
|
|
" bat3A.update(dt)\n",
|
|
" meanQ.append(np.mean([cc.Q for cc in bat3A.processing]))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 23,
|
|
"id": "a86acbef",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"-3502.2222222222213 1427.5555555555961 0\n",
|
|
"-3484.444444444443 1427.5555555555961 5\n",
|
|
"-3466.6666666666647 1427.5555555555961 10\n",
|
|
"-3448.8888888888864 1427.5555555555961 15\n",
|
|
"-3431.111111111108 1427.5555555555961 20\n",
|
|
"-3413.33333333333 1427.5555555555961 25\n",
|
|
"-3395.5555555555516 1427.5555555555961 30\n",
|
|
"-3377.7777777777733 1427.5555555555961 35\n",
|
|
"-3359.999999999995 1427.5555555555961 40\n",
|
|
"-3342.2222222222167 1427.5555555555961 45\n",
|
|
"-3324.4444444444384 1427.5555555555961 50\n",
|
|
"-3306.66666666666 1427.5555555555961 55\n",
|
|
"-3288.888888888882 1427.5555555555961 60\n",
|
|
"-3271.1111111111036 1427.5555555555961 65\n",
|
|
"-3253.3333333333253 1427.5555555555961 2\n",
|
|
"-3235.555555555547 1427.5555555555961 7\n",
|
|
"-3217.7777777777687 1427.5555555555961 12\n",
|
|
"-3199.9999999999905 1427.5555555555961 17\n",
|
|
"-3182.222222222212 1427.5555555555961 22\n",
|
|
"-3164.444444444434 1427.5555555555961 27\n",
|
|
"-3146.6666666666556 1427.5555555555961 32\n",
|
|
"-3128.8888888888773 1427.5555555555961 37\n",
|
|
"-3111.111111111099 1427.5555555555961 42\n",
|
|
"-3093.3333333333208 1427.5555555555961 47\n",
|
|
"-3075.5555555555425 1427.5555555555961 52\n",
|
|
"-3057.777777777764 1427.5555555555961 57\n",
|
|
"-3039.999999999986 1427.5555555555961 62\n",
|
|
"-3022.2222222222076 1427.5555555555961 4\n",
|
|
"-3004.4444444444293 1427.5555555555961 9\n",
|
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"-2986.666666666651 1427.5555555555961 14\n",
|
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"-2968.8888888888728 1427.5555555555961 19\n",
|
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"-2951.1111111110945 1427.5555555555961 24\n",
|
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"-2933.333333333316 1427.5555555555961 29\n",
|
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"-2915.555555555538 1427.5555555555961 34\n",
|
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"-2897.7777777777596 1427.5555555555961 39\n",
|
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"-2879.9999999999814 1427.5555555555961 44\n",
|
|
"-2862.222222222203 1427.5555555555961 49\n",
|
|
"-2844.444444444425 1427.5555555555961 54\n",
|
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"-2826.6666666666465 1427.5555555555961 59\n",
|
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"-2808.888888888868 1427.5555555555961 64\n",
|
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"-2791.11111111109 1427.5555555555961 1\n",
|
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"-2773.3333333333117 1427.5555555555961 6\n",
|
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"-2755.5555555555334 1427.5555555555961 11\n",
|
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"-2737.777777777755 1427.5555555555961 16\n",
|
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"-2719.999999999977 1427.5555555555961 21\n",
|
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"-2702.2222222221985 1427.5555555555961 26\n",
|
|
"-2684.4444444444202 1427.5555555555961 31\n",
|
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"-2666.666666666642 1427.5555555555961 36\n",
|
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"-2648.8888888888637 1427.5555555555961 41\n",
|
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"-2631.1111111110854 1427.5555555555961 46\n",
|
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"-2613.333333333307 1427.5555555555961 51\n",
|
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"-2595.555555555529 1427.5555555555961 56\n",
|
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"-2577.7777777777505 1427.5555555555961 61\n",
|
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"-2559.9999999999723 1427.5555555555961 3\n",
|
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"-2542.222222222194 1427.5555555555961 8\n",
|
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"-2524.4444444444157 1427.5555555555961 13\n",
|
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"-2506.6666666666374 1427.5555555555961 18\n",
|
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"-2488.888888888859 1427.5555555555961 23\n",
|
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"-2471.111111111081 1427.5555555555961 28\n",
|
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"-2453.3333333333026 1427.5555555555961 33\n",
|
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"-2435.5555555555243 1427.5555555555961 38\n",
|
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"-2417.777777777746 1427.5555555555961 43\n",
|
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"-2399.9999999999677 1427.5555555555961 48\n",
|
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"-2382.2222222221894 1427.5555555555961 53\n",
|
|
"-2364.444444444411 1427.5555555555961 58\n",
|
|
"-2346.666666666633 1427.5555555555961 63\n",
|
|
"-2328.8888888888546 1427.5555555555961 0\n",
|
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"-2311.1111111110763 1427.5555555555961 5\n",
|
|
"-2293.333333333298 1427.5555555555961 10\n",
|
|
"-2275.5555555555197 1427.5555555555961 15\n",
|
|
"-2257.7777777777414 1427.5555555555961 20\n",
|
|
"-2239.999999999963 1427.5555555555961 25\n",
|
|
"-2222.222222222185 1427.5555555555961 30\n",
|
|
"-2204.4444444444066 1427.5555555555961 35\n",
|
|
"-2186.6666666666283 1427.5555555555961 40\n",
|
|
"-2168.88888888885 1427.5555555555961 45\n",
|
|
"-2151.1111111110718 1427.5555555555961 50\n",
|
|
"-2133.3333333332935 1427.5555555555961 55\n",
|
|
"-2115.555555555515 1427.5555555555961 60\n",
|
|
"-2097.777777777737 1427.5555555555961 65\n",
|
|
"-2079.9999999999586 1427.5555555555961 2\n",
|
|
"-2062.2222222221803 1427.5555555555961 7\n",
|
|
"-2044.444444444402 1427.5555555555961 12\n",
|
|
"-2026.6666666666238 1427.5555555555961 17\n",
|
|
"-2008.8888888888455 1427.5555555555961 22\n",
|
|
"-1991.1111111110672 1427.5555555555961 27\n",
|
|
"-1973.333333333289 1427.5555555555961 32\n",
|
|
"-1955.5555555555106 1427.5555555555961 37\n",
|
|
"-1937.7777777777324 1427.5555555555961 42\n",
|
|
"-1919.999999999954 1427.5555555555961 47\n",
|
|
"-1902.2222222221758 1427.5555555555961 52\n",
|
|
"-1884.4444444443975 1427.5555555555961 57\n",
|
|
"-1866.6666666666192 1427.5555555555961 62\n",
|
|
"-1848.888888888841 1427.5555555555961 4\n",
|
|
"-1831.1111111110627 1427.5555555555961 9\n",
|
|
"-1813.3333333332844 1427.5555555555961 14\n",
|
|
"-1795.555555555506 1427.5555555555961 19\n",
|
|
"-1777.7777777777278 1427.5555555555961 24\n",
|
|
"-1759.9999999999495 1427.5555555555961 29\n",
|
|
"-1742.2222222221712 1427.5555555555961 34\n",
|
|
"-1724.444444444393 1427.5555555555961 39\n",
|
|
"-1706.6666666666147 1427.5555555555961 44\n",
|
|
"-1688.8888888888364 1427.5555555555961 49\n",
|
|
"-1671.111111111058 1427.5555555555961 54\n",
|
|
"-1653.3333333332798 1427.5555555555961 59\n",
|
|
"-1635.5555555555015 1427.5555555555961 64\n",
|
|
"-1617.7777777777233 1427.5555555555961 1\n",
|
|
"-1599.999999999945 1427.5555555555961 6\n",
|
|
"-1582.2222222221667 1427.5555555555961 11\n",
|
|
"-1564.4444444443884 1427.5555555555961 16\n",
|
|
"-1546.6666666666101 1427.5555555555961 21\n",
|
|
"-1528.8888888888318 1427.5555555555961 26\n",
|
|
"-1511.1111111110536 1427.5555555555961 31\n",
|
|
"-1493.3333333332753 1427.5555555555961 36\n",
|
|
"-1475.555555555497 1427.5555555555961 41\n",
|
|
"-1457.7777777777187 1427.5555555555961 46\n",
|
|
"-1439.9999999999404 1427.5555555555961 51\n",
|
|
"-1422.2222222221621 1427.5555555555961 56\n",
|
|
"-1404.4444444443839 1427.5555555555961 61\n",
|
|
"-1386.6666666666056 1427.5555555555961 3\n",
|
|
"-1368.8888888888273 1427.5555555555961 8\n",
|
|
"-1351.111111111049 1427.5555555555961 13\n",
|
|
"-1333.3333333332707 1427.5555555555961 18\n",
|
|
"-1315.5555555554924 1427.5555555555957 23\n",
|
|
"-1297.7777777777142 1427.5555555555943 28\n",
|
|
"-1279.9999999999359 1427.5555555555932 33\n",
|
|
"-1262.2222222221576 1427.5555555555918 38\n",
|
|
"-1244.4444444443793 1427.5555555555907 43\n",
|
|
"-1226.666666666601 1427.5555555555893 48\n",
|
|
"-1208.8888888888227 1427.5555555555882 53\n",
|
|
"-1191.1111111110445 1427.5555555555868 58\n",
|
|
"-1173.3333333332662 1427.5555555555857 63\n",
|
|
"-1155.555555555488 1427.8259259259546 0\n",
|
|
"-1137.7777777777096 1427.609629629657 5\n",
|
|
"-1119.9999999999313 1427.880000000026 10\n",
|
|
"-1102.222222222153 1427.6637037037285 15\n",
|
|
"-1084.4444444443748 1427.9340740740975 20\n",
|
|
"-1066.6666666665965 1427.7177777778 25\n",
|
|
"-1048.8888888888182 1427.9881481481689 30\n",
|
|
"-1031.11111111104 1427.7718518518714 35\n",
|
|
"-1013.3333333332615 1427.5555555555736 40\n",
|
|
"-995.5555555554832 1427.8259259259428 45\n",
|
|
"-977.777777777705 1425.8408740740929 50\n",
|
|
"-959.9999999999267 1424.071244444466 55\n",
|
|
"-942.2222222221484 1421.8602814815067 60\n",
|
|
"-924.4444444443701 1420.0906518518807 65\n",
|
|
"-906.6666666665918 1417.1275522222538 2\n",
|
|
"-888.8888888888135 1413.3689225926255 7\n",
|
|
"-871.1111111110353 1409.2131596296638 12\n",
|
|
"-853.333333333257 1405.0573966667018 17\n",
|
|
"-835.5555555554787 1401.2987670370744 22\n",
|
|
"-817.7777777777004 1397.1430040741136 27\n",
|
|
"-799.9999999999221 1391.8422855555928 32\n",
|
|
"-782.2222222221438 1385.6918559259593 37\n",
|
|
"-764.4444444443656 1379.8932262963258 42\n",
|
|
"-746.6666666665873 1373.0224244444703 47\n",
|
|
"-728.888888888809 1365.3187948148375 52\n",
|
|
"-711.1111111110307 1357.305698518538 57\n",
|
|
"-693.3333333332524 1349.2926022222387 62\n",
|
|
"-675.5555555554741 1341.5889725926056 4\n",
|
|
"-657.7777777776959 1331.9683896296428 9\n",
|
|
"-639.9999999999176 1322.4107600000093 14\n",
|
|
"-622.2222222221393 1667.5016637037595 19\n",
|
|
"-604.444444444361 1657.944034074126 24\n",
|
|
"-586.6666666665827 1648.1181377778269 29\n",
|
|
"-568.8888888888044 1638.5605081481988 34\n",
|
|
"-551.1111111110262 1628.734611851904 39\n",
|
|
"-533.3333333332479 1620.1664688889448 44\n",
|
|
"-515.5555555554696 1612.153372592654 49\n",
|
|
"-497.7777777776913 1604.449742963034 54\n",
|
|
"-479.9999999999131 1596.4366466667504 59\n",
|
|
"-462.2222222221354 1588.4235503704685 64\n",
|
|
"-444.4444444443577 1580.7199207408544 1\n",
|
|
"-426.66666666658 1572.7068244445734 6\n",
|
|
"-408.8888888888023 1565.0031948149483 11\n",
|
|
"-391.11111111102457 1556.9900985186496 16\n",
|
|
"-373.3333333332469 1550.303174444573 21\n",
|
|
"-355.5555555554692 1544.1527448149402 26\n",
|
|
"-337.7777777776915 1538.3541151853078 31\n",
|
|
"-319.9999999999138 1532.2036855556753 36\n",
|
|
"-302.2222222221361 1526.0532559260425 41\n",
|
|
"-284.4444444443584 1520.25462629641 46\n",
|
|
"-266.66666666658074 1514.1041966667774 51\n",
|
|
"-248.88888888880302 1508.3055670371448 56\n",
|
|
"-231.11111111102534 1502.155137407512 61\n",
|
|
"-213.33333333324762 1496.3565077778799 3\n",
|
|
"-195.55555555546994 1490.2060781482476 8\n",
|
|
"-177.77777777769222 1484.4074485186154 13\n",
|
|
"-159.99999999991454 1478.2570188889813 18\n",
|
|
"-142.22222222213685 1472.152678148243 23\n",
|
|
"-124.44444444435915 1468.3940485186115 28\n",
|
|
"-106.66666666658134 1464.2382855556464 33\n",
|
|
"-88.88888888880348 1460.4796559260142 38\n",
|
|
"-71.11111111102564 1456.3238929630525 43\n",
|
|
"-53.33333333324783 1452.5652633334244 48\n",
|
|
"-35.555555555470065 1448.4095003704558 53\n",
|
|
"-17.777777777692293 1444.6508707408184 58\n",
|
|
"8.548203811464816e-11 1440.4951077778505 63\n",
|
|
"18.000000000085464 1436.0689744445178 0\n",
|
|
"35.60000000008548 1432.5266411111847 5\n",
|
|
"53.6000000000856 1428.1005077778507 10\n",
|
|
"71.20000000008552 1424.5581744445174 15\n",
|
|
"89.20000000008534 1420.132041111184 20\n",
|
|
"106.80000000008516 1417.6512444445186 25\n",
|
|
"124.80000000008513 1415.169911111187 30\n",
|
|
"142.40000000008556 1413.6165777778535 35\n",
|
|
"160.00000000008595 1411.621911111187 40\n",
|
|
"178.00000000008637 1409.1405777778564 45\n",
|
|
"195.60000000008677 1409.3560000000828 50\n",
|
|
"213.6000000000872 1408.9146666667523 55\n",
|
|
"231.20000000008758 1409.3560000000873 60\n",
|
|
"249.20000000008798 1408.914666666763 65\n",
|
|
"266.8000000000884 1410.1081366667718 2\n",
|
|
"284.8000000000888 1411.6558033334436 7\n",
|
|
"302.4000000000892 1414.041936666781 12\n",
|
|
"320.00000000008964 1415.986736666785 17\n",
|
|
"338.00000000009004 1417.5793022223445 22\n",
|
|
"355.60000000009046 1422.0054355556776 27\n",
|
|
"373.60000000009086 1427.0898577778985 32\n",
|
|
"391.2000000000913 1433.5106577778974 37\n",
|
|
"409.2000000000917 1439.0929911112298 42\n",
|
|
"426.8000000000921 1446.2341633334515 47\n",
|
|
"444.8000000000925 1453.7214966667843 52\n",
|
|
"462.4000000000929 1462.0049633334509 57\n",
|
|
"480.0000000000933 1469.8017633334505 62\n",
|
|
"498.0000000000913 1477.289096666785 4\n",
|
|
"515.6000000000894 1487.18005000012 9\n",
|
|
"533.6000000000873 1656.0847433334857 14\n",
|
|
"1080.4000000000592 1305.2162100002315 19\n",
|
|
"1098.4000000000622 1308.6439433335693 24\n",
|
|
"1116.0000000000648 1313.6983555557956 29\n",
|
|
"1134.0000000000678 1318.3903555557997 34\n",
|
|
"1151.6000000000704 1323.7316222224704 39\n",
|
|
"1169.6000000000734 1327.4341355558079 44\n",
|
|
"1187.200000000076 1330.9626022224786 49\n",
|
|
"1205.200000000079 1333.8006022224827 54\n",
|
|
"1222.8000000000816 1336.9480688891533 59\n",
|
|
"1240.4000000000842 1340.476535555824 64\n",
|
|
"1258.4000000000872 1344.6857733335992 1\n",
|
|
"1276.0000000000898 1349.7562400002637 6\n",
|
|
"1294.0000000000928 1354.1019733335952 11\n",
|
|
"1311.6000000000954 1359.172440000257 16\n",
|
|
"1329.6000000000984 1362.501467778029 21\n",
|
|
"1347.200000000101 1366.164851111358 26\n",
|
|
"1365.200000000104 1370.1455844446893 31\n",
|
|
"1382.8000000001066 1374.4781177780208 36\n",
|
|
"1400.4000000001092 1379.260917778019 41\n",
|
|
"1418.4000000001122 1383.2416511113502 46\n",
|
|
"1436.0000000001148 1389.299057778014 51\n",
|
|
"1454.0000000001178 1394.881391111344 56\n",
|
|
"1471.6000000001204 1401.3021911113408 61\n",
|
|
"1489.6000000001234 1406.8845244446707 3\n",
|
|
"1507.200000000126 1413.3053244446671 8\n",
|
|
"1525.200000000129 1418.8876577779968 13\n",
|
|
"1542.8000000001316 1424.8217911113268 18\n",
|
|
"1560.4000000001342 1431.1965022224356 23\n",
|
|
"1578.4000000001372 1434.7388355557662 28\n",
|
|
"1596.0000000001398 1439.1649688890968 33\n",
|
|
"1614.0000000001428 1442.7073022224297 38\n",
|
|
"1631.6000000001454 1447.1334355557651 43\n",
|
|
"1649.6000000001484 1450.6757688891005 48\n",
|
|
"1667.200000000151 1455.101902222436 53\n",
|
|
"1685.200000000154 1458.644235555771 58\n",
|
|
"1702.8000000001566 1462.5837022224391 63\n",
|
|
"1720.4000000001593 1467.009835555771 0\n",
|
|
"1738.4000000001622 1470.552168889101 5\n",
|
|
"1756.0000000001648 1474.9783022224312 10\n",
|
|
"1774.0000000001678 1478.5206355557616 15\n",
|
|
"1791.6000000001704 1482.9467688890918 20\n",
|
|
"1809.6000000001734 1485.427565555757 25\n",
|
|
"1827.200000000176 1487.9088988890899 30\n",
|
|
"1845.200000000179 1489.462232222423 35\n",
|
|
"1862.8000000001816 1491.4568988890883 40\n",
|
|
"1880.4000000001843 1493.9382322224205 45\n",
|
|
"1898.4000000001872 1495.4915655557527 50\n",
|
|
"1916.0000000001899 1497.972898889085 55\n",
|
|
"1934.0000000001928 1499.5262322224169 60\n",
|
|
"1951.6000000001955 1502.0075655557491 65\n",
|
|
"1969.6000000001984 1503.5608988890815 2\n",
|
|
"1987.200000000201 1506.042232222417 7\n",
|
|
"2005.200000000204 1507.5955655557525 12\n",
|
|
"2022.8000000002066 1509.5902322224215 17\n",
|
|
"2040.4000000002093 1512.0266666668683 22\n",
|
|
"2058.400000000212 1511.5400000002041 27\n",
|
|
"2076.000000000215 1512.0266666668733 32\n",
|
|
"2094.000000000218 1511.5400000002091 37\n",
|
|
"2111.6000000002205 1512.0266666668783 42\n",
|
|
"2129.600000000223 1511.5400000002144 47\n",
|
|
"2147.2000000002263 1512.0266666668836 52\n",
|
|
"2165.200000000229 1511.5400000002194 57\n",
|
|
"2182.8000000002316 1511.5400000002223 62\n",
|
|
"2200.4000000002343 1512.0266666668908 4\n",
|
|
"2218.400000000237 1511.540000000226 9\n",
|
|
"2400.4000000002657 1352.4633066668803 14\n",
|
|
"2418.4000000002684 1358.0246400002125 19\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"for cc in bat3A.product:\n",
|
|
" print(cc.t_charge * 60, cc.Q, cc.idx_oven)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 24,
|
|
"id": "1179dfeb",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([[-1. , 3. , 3. , 4.33333333, 4.33333333,\n",
|
|
" 6. , 6. , 7. , 7. , 8.33333333,\n",
|
|
" 8.33333333, 19.33333333, 19.33333333, 22. , 22. ,\n",
|
|
" 26. , 26. , 30. , 30. , 34. ,\n",
|
|
" 34. , 38. , 28. , 33. , 33. ,\n",
|
|
" 34. , 34. , 35. , 35. , 36.33333333,\n",
|
|
" 36.33333333, 40.66666667, 40.66666667, 43. , 43. ,\n",
|
|
" 44.66666667, 44.66666667, 46. , 46. , 51. ],\n",
|
|
" [73. , 73. , 66.2 , 66.2 , 59.57 ,\n",
|
|
" 59.57 , 52.77 , 52.77 , 46.42 , 46.42 ,\n",
|
|
" 40.24 , 40.24 , 46.42 , 46.42 , 52.77 ,\n",
|
|
" 52.77 , 59.57 , 59.57 , 66.2 , 66.2 ,\n",
|
|
" 73. , 73. , 73. , 73. , 67.54 ,\n",
|
|
" 67.54 , 62.29 , 62.29 , 57.15 , 57.15 ,\n",
|
|
" 52.84 , 52.84 , 57.15 , 57.15 , 62.29 ,\n",
|
|
" 62.29 , 67.54 , 67.54 , 73. , 73. ]])"
|
|
]
|
|
},
|
|
"execution_count": 24,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"example_program"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 25,
|
|
"id": "3ed23b12",
|
|
"metadata": {
|
|
"scrolled": false
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"application/vnd.jupyter.widget-view+json": {
|
|
"model_id": "a0fd2eb2d1424e2ea51e10140d00a855",
|
|
"version_major": 2,
|
|
"version_minor": 0
|
|
},
|
|
"image/png": 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"\n",
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" <div style=\"display: inline-block;\">\n",
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" <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
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" Figure\n",
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" </div>\n",
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' width=1100.0/>\n",
|
|
" </div>\n",
|
|
" "
|
|
],
|
|
"text/plain": [
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"fig, ax = plt.subplots(1, 1, figsize=(11, 7), sharex=True)\n",
|
|
"ax.plot(*np.array([(cc.t_push, cc.Q) for cc in bat3A.product]).T, '.')\n",
|
|
"ax.set_ylim(ymin=0)\n",
|
|
"\n",
|
|
"ax.plot(np.arange(0, n_steps) * dt, meanQ)\n",
|
|
"\n",
|
|
"twin = ax.twinx()\n",
|
|
"twin.plot(sample_time, np.interp(sample_time, *example_program), '-')\n",
|
|
"twin.set_ylim(ymin=0)\n",
|
|
"twin.grid()\n",
|
|
"\n",
|
|
"for x in [9, 9+9, 24+13, 24+13+3]:\n",
|
|
" ax.axvline(x, linestyle=\":\")\n",
|
|
"\n",
|
|
"# ax2.plot(sample_time, sample_charging.period(sample_time))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 26,
|
|
"id": "4df78f65",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"1425.6"
|
|
]
|
|
},
|
|
"execution_count": 26,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"72 * 24*66/80"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 27,
|
|
"id": "2065d0c6",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import numpy as np\n",
|
|
"\n",
|
|
"T104 = np.array('''\\\n",
|
|
"6.469635511825288 97.62584917278241\n",
|
|
"16.728957359665642 99.54879021268471\n",
|
|
"18.569715003482443 103.65207384901169\n",
|
|
"20.23392722854227 114.40742124017106\n",
|
|
"21.935674341607154 161.14094501700924\n",
|
|
"22.981977601017448 195.1785155500827\n",
|
|
"24.15864522242518 235.88581465069137\n",
|
|
"25.640236342576202 287.9364470509861\n",
|
|
"26.945866244561714 343.30806423935337\n",
|
|
"28.33778257391458 406.679318037288\n",
|
|
"29.817737932409315 468.0569715445107\n",
|
|
"31.561459857974853 525.452471559652\n",
|
|
"32.95804979205987 562.1750936235078\n",
|
|
"34.530951464665264 593.578083519235\n",
|
|
"35.973605615391534 617.645129054075\n",
|
|
"37.811559096369066 637.7375917308494\n",
|
|
"40.00038345261282 657.184026971646\n",
|
|
"41.97057073748064 673.2867655223238\n",
|
|
"43.634899802658765 683.3758971201314\n",
|
|
"47.226156098902706 706.2341647571851\n",
|
|
"51.91258403403752 734.4852473578494\n",
|
|
"55.9423997143347 756.7025346482691\n",
|
|
"59.841383672161214 774.9149565445614\n",
|
|
"65.36295556290182 791.2221022136539\n",
|
|
"72.37558262337606 805.6164010215316\n",
|
|
"77.7223616971342 818.5823735451772\n",
|
|
"83.15823136109901 823.5588036379428\n",
|
|
"86.27058922244535 827.0690542763996\n",
|
|
"89.99431300281623 844.605166200653\n",
|
|
"93.27632271593967 880.7700848920435\n",
|
|
"97.5625440358545 940.9768136715566\n",
|
|
"'''.split(), dtype=np.double).reshape((-1, 2))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 28,
|
|
"id": "315b9960",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import numpy as np\n",
|
|
"\n",
|
|
"T105 = np.array('''\\\n",
|
|
"6.294258494251331 97.61575499409514\n",
|
|
"19.70919825724002 106.38254918388611\n",
|
|
"32.511720540139464 107.11942422804805\n",
|
|
"36.45022566798224 149.9843540230354\n",
|
|
"37.762982817184295 164.7168078169325\n",
|
|
"38.89966190810257 183.43646219225434\n",
|
|
"41.784269168845285 235.5678480220463\n",
|
|
"45.14555490223785 319.7053509241225\n",
|
|
"47.54530488204948 386.4657252162683\n",
|
|
"49.4653385461354 438.54159306328097\n",
|
|
"52.87070221415806 521.3491879233252\n",
|
|
"54.530007154249105 560.0855986352677\n",
|
|
"57.50171872318727 615.553110521163\n",
|
|
"60.12571410005344 653.678823422533\n",
|
|
"64.32646687342904 701.2224050390148\n",
|
|
"68.5287385683426 740.1051813419208\n",
|
|
"72.20780021349182 762.3022802749662\n",
|
|
"76.85155229541621 783.8886813974389\n",
|
|
"81.67184979609755 798.823018765079\n",
|
|
"84.03850481239965 804.2890165241714\n",
|
|
"85.9656657237021 815.7257209767135\n",
|
|
"87.71628121624755 833.8144891840884\n",
|
|
"89.90487189225468 854.5933560115893\n",
|
|
"91.56756519577655 874.0095087163243\n",
|
|
"93.75580535142879 896.7870229238808\n",
|
|
"95.59364199228798 917.545701394007\n",
|
|
"97.60662197048458 939.6469056295243\n",
|
|
"'''.split(), dtype=np.double).reshape((-1, 2))\n",
|
|
"\n",
|
|
"progress = np.linspace(0, 100, 1001)\n",
|
|
"mean = (np.interp(progress, *T104.T) + np.interp(progress, *T105.T))/2"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 29,
|
|
"id": "85cbc85b",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.legend.Legend at 0x1fdde771910>"
|
|
]
|
|
},
|
|
"execution_count": 29,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"application/vnd.jupyter.widget-view+json": {
|
|
"model_id": "3650fe93b69b4fa39ee546b02945b526",
|
|
"version_major": 2,
|
|
"version_minor": 0
|
|
},
|
|
"image/png": 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",
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"\n",
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" <div style=\"display: inline-block;\">\n",
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" <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
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" Figure\n",
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" </div>\n",
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' width=640.0/>\n",
|
|
" </div>\n",
|
|
" "
|
|
],
|
|
"text/plain": [
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.figure()\n",
|
|
"plt.plot(*T104.T, label=\"104 side\")\n",
|
|
"plt.plot(*T105.T, label=\"105 side\")\n",
|
|
"plt.plot(progress, mean, label=\"mean\")\n",
|
|
"plt.legend()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 30,
|
|
"id": "1ea1b3e5",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"table1 = np.array('''\\\n",
|
|
"8.40 \t1set\t\t1Set\t-360\t820\n",
|
|
"7.98 \t2Set\t\t2Set\t-160\t700\n",
|
|
"7.45 \t3set\t\t3Set\t40\t540\n",
|
|
"4.30 \t4Set\t\t4Set\t240\t380\n",
|
|
"1.77 \t5Set\t\t5Set\t480\t180\n",
|
|
"'''.split()).reshape((5,-1))[:,[0,-2,-1]].astype(np.double)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 31,
|
|
"id": "245eff1f",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def heat_table_to_curve (table, heat_base, start, duration, ):\n",
|
|
" \n",
|
|
" if not (table.shape[1] == 3):\n",
|
|
" return None\n",
|
|
" \n",
|
|
" dQ = table.T[0]\n",
|
|
" \n",
|
|
" step_times = np.concatenate((start + table.T[1], start + duration + table[::-1, 2]))\n",
|
|
" \n",
|
|
" step0 = np.cumsum(dQ) - dQ\n",
|
|
" step1 = np.cumsum(dQ)\n",
|
|
" \n",
|
|
" print(step0)\n",
|
|
" print(step1)\n",
|
|
" \n",
|
|
" steps_decreasing = list(zip(-step0, -step1))\n",
|
|
" steps_increasing = list(zip(-step1[::-1], -step0[::-1]))\n",
|
|
" \n",
|
|
" steps = steps_decreasing + steps_increasing\n",
|
|
" \n",
|
|
" return np.array([ (step_times[i], s0 + heat_base, step_times[i], s1 + heat_base)\n",
|
|
" for i, (s0, s1) in enumerate(steps) ]).reshape((-1, 2))\n",
|
|
" "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 32,
|
|
"id": "d79e655e",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"[ 0. 8.4 16.38 23.83 28.13]\n",
|
|
"[ 8.4 16.38 23.83 28.13 29.9 ]\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"curve1 = heat_table_to_curve(table1, 81, 8*60, 12*60)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 33,
|
|
"id": "1a04c477",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"(5, 3)"
|
|
]
|
|
},
|
|
"execution_count": 33,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"np.array('''\\\n",
|
|
"7.30 \t1set\t\t1Set\t-340\t380\n",
|
|
"5.64 \t2Set\t\t2Set\t-180\t220\n",
|
|
"4.14 \t3set\t\t3Set\t-20\t60\n",
|
|
"'''.split()).reshape((5,-1)).shape"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 34,
|
|
"id": "51040443",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"[ 0. 7.3 12.94]\n",
|
|
"[ 7.3 12.94 17.08]\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"table2 = np.array('''\\\n",
|
|
"7.30 \t1set\t\t1Set\t-340\t380\n",
|
|
"5.64 \t2Set\t\t2Set\t-180\t220\n",
|
|
"4.14 \t3set\t\t3Set\t-20\t60\n",
|
|
"'''.split()).reshape((3,-1))[:,[0,-2,-1]].astype(np.double)\n",
|
|
"\n",
|
|
"curve2 = heat_table_to_curve(table2, 81, (24+13)*60, 4.5*60)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 35,
|
|
"id": "37535ff4",
|
|
"metadata": {
|
|
"scrolled": false
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"application/vnd.jupyter.widget-view+json": {
|
|
"model_id": "8233437e227f45ecbd4609561dc4167c",
|
|
"version_major": 2,
|
|
"version_minor": 0
|
|
},
|
|
"image/png": 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",
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"\n",
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" <div style=\"display: inline-block;\">\n",
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" <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
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" Figure\n",
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" </div>\n",
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' width=1019.9878861296182/>\n",
|
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" </div>\n",
|
|
" "
|
|
],
|
|
"text/plain": [
|
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"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.figure(figsize=(33.68/2.54/1.3, 11.85/2.54/1.3))\n",
|
|
"plt.plot(curve1.T[0], curve1.T[1] )\n",
|
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"plt.plot(curve2.T[0], curve2.T[1] )\n",
|
|
"plt.xlim(0, 58)\n",
|
|
"plt.xticks(np.arange(0, 59) * 60, np.arange(0, 59), rotation=90)\n",
|
|
"plt.grid()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "73a80793",
|
|
"metadata": {},
|
|
"source": [
|
|
"# 원본 엑셀 매크로"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 36,
|
|
"id": "32f3b457",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"(0.0, (81, 69.61621621621622))\n",
|
|
"(3.5, (69.61621621621622, 58.83157894736841))\n",
|
|
"(7.0, (58.83157894736841, 48.599999999999994))\n",
|
|
"(10.5, (48.599999999999994, 42.038999999999994))\n",
|
|
"(14.5, (42.038999999999994, 38.879999999999995))\n",
|
|
"(24.5, (38.879999999999995, 42.038999999999994))\n",
|
|
"(27.75, (42.038999999999994, 48.599999999999994))\n",
|
|
"(30.35, (48.599999999999994, 58.83157894736841))\n",
|
|
"(32.43, (58.83157894736841, 69.61621621621622))\n",
|
|
"(34.094, (69.61621621621622, 81))\n",
|
|
"(36.4668813559322, (81, 72.9))\n",
|
|
"(39.4668813559322, (72.9, 67.22999999999999))\n",
|
|
"(42.4668813559322, (67.22999999999999, 62.370000000000005))\n",
|
|
"(47.4668813559322, (62.370000000000005, 67.22999999999999))\n",
|
|
"(50.4668813559322, (67.22999999999999, 72.9))\n",
|
|
"(53.4668813559322, (72.9, 81))\n"
|
|
]
|
|
},
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"C:\\Users\\RIST\\AppData\\Local\\Temp\\ipykernel_94484\\1486307578.py:134: MatplotlibDeprecationWarning: The 'b' parameter of grid() has been renamed 'visible' since Matplotlib 3.5; support for the old name will be dropped two minor releases later.\n",
|
|
" plt.grid(b=True, which='minor', color='r', linestyle='--')\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"(1120.0, 1320.0)"
|
|
]
|
|
},
|
|
"execution_count": 36,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"application/vnd.jupyter.widget-view+json": {
|
|
"model_id": "c2fb98b39e5647488aa1fb23b5c9e196",
|
|
"version_major": 2,
|
|
"version_minor": 0
|
|
},
|
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"image/png": 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",
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"\n",
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" <div style=\"display: inline-block;\">\n",
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" <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
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" Figure\n",
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" </div>\n",
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" <img 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xUsFmDxYvu2Fc8yLTEyGm/I1KOKRkanBx/oXWg1Mjo9eCej04MP9E67RkYXrd69vtRl36qOd51pk2aNyyumXl8auf0uUPlF+vgD2l5H1XxQefxJUFdXh5EjR2LRokVej5988slYtGgRtm3bhu+++w4DBgxAbm4uDh8+7IiZM2cOli9fjvfeew/fffcdamtrcdFFF8FmszliZs6ciaKiIuTn5yM/Px9FRUW49tprO5V7xBDuVepIaCktLbWv1FhcbC+oqhICsG9b8SzTEuNHU9dodVvBVrZei8UiVqxYISwWS4fybaMLhEYmPy0aP/nRu861SSkf6F1YfQjlWIo27+hD5zSubxCoa7SG3Ls6U7zz/IePqeNdkHxoT1N3+JjTC1N85Pa7IHkXKT64jSmP66iad6qNv5KSEs2ruAMQy5cvbzemqqpKABBr1qwRQghx/PhxYTKZxHvvveeIOXDggIiJiRH5+flCCOF469SGDRscMevXrxcAxM6dOzucZ6TBJ+iEEEIIIYQQQgKKxWLBK6+8gvT0dIwcORIAsGnTJlitVuTm5jrisrOzMWzYMKxbtw4AsH79eqSnp7t9LH7ChAlIT093xEQz/A46IYQQQgghhOiYmpoax+uYgbavau4IK1euxFVXXQWz2YysrCysXr0aGRkZAICKigrExcWha9eubppevXqhoqLCEdOzZ8829fbs2dMRE83wCbpeMRqd29xc5763Mi0xMhpfefmrRxWNjE4PPtC70GpkdHrwTkanBx/onXaNjC5avZs8uXO5yegiwQfPmMmTI7ffBSq/SB9/QNvrqJoPio6/nJwcpKenO36eeOIJ3zn54ZxzzkFRURHWrVuHqVOn4oorrsChQ4fa1QghYDAYHPuu/+8rJlrhE3S9kpRk3yYnA6tWuR/zLNMS40/ja/VkmXpU0cjotGj85Ufvgp+fyhoZnR68k9Hp4T7EPqRdI6OLVu8++cS5inRykjreeYsJtsb1PvDJJ+2v4q5yvwtUfpE+/oC211E1HxQdf8XFxejdu7djX+vTc/upknHSSSfhpJNOwoQJEzBo0CAsWbIE8+bNQ2ZmJiwWCyorK92eoh86dAinn346ACAzMxMHDx5sU+/hw4fRq1cvzXlFCnyCrldaV3BsbATy8uzbVjzLtMTIaLwhU48qGhmdHnygd6HVyOj04J2MTg8+0DvtGhldtHr3+EKXfYs63nWmTZo1LitaP74wcvtdoPKL9PEHtL2Oqvmg6PhLTU1FWlqa46czE3RPhBBobDnvqaeeCpPJhNWrVzuOl5eXY/v27Y4J+sSJE1FVVYWCggJHzA8//ICqqipHTFQT5kXqSIjhKu7qrkDKVdx1uIotvQurD1zFnX0oKD5IaLiKe2j7EFdxj/7xx1XcQ7eKe01NjdiyZYvYsmWLACCeeeYZsWXLFrF3715RW1sr5s2bJ9avXy9+++03sWnTJnHzzTeL+Ph4sX37dkcdf/zjH0WfPn3EmjVrxObNm8W5554rRo4cKZqamhwxU6dOFSNGjBDr168X69evF8OHDxcXXXSRVI6RDj/iTgghhBBCCCHEL4WFhTjnnHMc+/fccw8A4Prrr8dLL72EnTt3YunSpThy5Ai6d++O0047Df/9738xdOhQh+bZZ59FbGwsrrjiCtTX12Py5Ml4/fXXYXT5fvzbb7+NO++807Ha+/Tp032+ez3a4ASdEEIIIYQQQohfJk2aBCGEz+PLli3zW0dCQgKef/55PP/88z5junXrhrfeektTjpEOv4OuV0wm5/bmm5373sq0xMhofOXlrx5VNDI6PfhA70KrkdHpwTsZnR58oHfaNTK6aPXuuus7l5uMLhJ88Iy57vrI7XeByi/Sxx/Q9jqq5oPK44+oQbg/Y09Ci+M76JLfMwkWPr/76Qev3wEKkk5VDb0LvUb1/FTWqJxfKMdStHkXSo3q+WnReP0OehDO40vn2ve9nV9l7wKtac8LFfILt0b1/Lx+B93PmAq3d6qNv45+B50EHz5B1ysNDfZtfT1wyy32bSueZVpiZDTekKlHFY2MTg8+0LvQamR0evBORqcHH+iddo2MLlq9m32Hy36DOt51pk2aNQ3Ostl3RG6/C1R+kT7+gLbXUTUfVB5/RAk4QdcrVqtzu2SJc99bmZYYGY2vvPzVo4pGRqcHH+hdaDUyOj14J6PTgw/0TrtGRhet3r2xtHO5yegiwQfPmDeWRm6/C1R+kT7+gLbXUTUfVB5/RAk4QSeEEEIIIYQQQhSAE3RCCCGEEEIIIUQBOEHXK/Hxzu38+c59b2VaYmQ0vvLyV48qGhmdHnygd6HVyOj04J2MTg8+0DvtGhldtHo374HO5SajiwQfPGPmPRC5/S5Q+UX6+APaXkfVfFB5/BE1CPcqdSS0cBV3dVcgVXHlaa26aNOonp/KGpXz4yrukaFRPT+u4h7ZGq7irs65uIp7aPPjKu7qwifoesVstm/r6oApU+zbVjzLtMTIaLwhU48qGhmdHnygd6HVyOj04J2MTg8+0DvtGhldtHp3ySUu+2Z1vOtMmzRrzM6ySy6J3H4XqPwiffwBba+jaj6oPP6IEnCCrldsNuf2yy+d+97KtMTIaHzl5a8eVTQyOj34QO9Cq5HR6cE7GZ0efKB32jUyumj17quvOpebjC4SfPCM+eqryO13gcov0scf0PY6quaDyuOPKAEn6IQQQgghhBBCiAJwgk4IIYQQQgghhCgAJ+h6JSHBuX31Vee+tzItMTIaX3n5q0cVjYxODz7Qu9BqZHR68E5Gpwcf6J12jYwuWr1b9K/O5SajiwQfPGMW/Sty+12g8ov08Qe0vY6q+aDy+CNqEO5V6kho4Sru6q5AquLK01p10aZRPT+VNSrnx1XcI0Ojen5cxT2yNVzFXZ1zcRX30ObHVdzVhU/Q9UrrCo61tcDQofZtK55lWmJkNN6QqUcVjYxODz7Qu9BqZHR68E5Gpwcf6J12jYwuWr0bO9Zlv04d7zrTJs0alxWtx46N3H4XqPwiffwBba+jaj6oPP6IEnCCrleam53b4mLnvrcyLTEyGl95+atHFY2MTg8+0LvQamR0evBORqcHH+iddo2MLlq927mzc7nJ6CLBB8+YnTsjt98FKr9IH39A2+uomg8qjz+iBJygE0IIIYQQQgghCsAJOiGEEEIIIYQQogCcoOuVxET7NikJyM+3b1vxLNMSI6Pxhkw9qmhkdHrwgd6FViOj04N3Mjo9+EDvtGtkdNHq3YoVLvuJ6njXmTZp1iQ6y1asiNx+F6j8In38AW2vo2o+qDz+iBLEhjsBEiZiY53bKVPaHnMt0xLjT2Np8p2Xv3pU0cjotGj85Ufvgp+fyhoZnR68k9Hp4T7EPqRdI6OLVu/OOw/4dpX288joIsGHKVPc7wPnnef891GwcpPRRYp3ndHI6LT64HkdVfNB5fFHlIBP0PVKTY19W10NpKXZt614lmmJkdF4Q6YeVTQyOj34QO9Cq5HR6cE7GZ0efKB32jUyumj1LjPLZb9GHe860ybNmhpnWWZW5Pa7QOUX6eMPaHsdVfNB5fFHlCAm3AkQBaip8V+mJUZGI5OPyhoZnR58oHeh1cjo9OCdjE4PPtA77RoZXTR6V6uwd95iQqXx9CVY55HRRZp3Kvng7Tqq5IPq44+EHU7QCSGEEEIIIYQQBeAEnRBCCCGEEEIIUQBO0PVK6wqOycnA9u32bSueZVpiZDTekKlHFY2MTg8+0LvQamR0evBORqcHH+iddo2MLlq9K9josp+kjnedaZNmjcuK1gUbI7ffBSq/SB9/QNvrqJoPKo8/ogScoOuVmBjntm9f5763Mi0xMhpfefmrRxWNjE4PPtC70GpkdHrwTkanBx/onXaNjC5avevTp3O5yegiwQfPmD59IrffBSq/SB9/QNvrqJoPKo8/ogS8Qnqltta+rakB0tPdF43wLNMSI6Pxhkw9qmhkdHrwgd6FViOj04N3Mjo9+EDvtGtkdNHqXbbLKtI1tep415k2adbUOsuysyK33wUqv0gff0Db66iaDyqPP6IEnKATQgghhBBCCCEKwAk6IYQQQgghhBC/fPvtt7j44ouRnZ0Ng8GAFStWOI5ZrVbMnTsXw4cPR3JyMrKzs3HdddehrKzMEfPbb7/BYDB4/fnwww8dcQMGDGhz/P777w9lU8NGbLgTIIQQQggh4cFstQGmeMBiAyxNAACrtQmNNsBsaYJJGOzHPGI8ywKicYlJFAKGMPhBogMhBOo19DtHfw2ABvA+lsymhDA4Ejjq6uowcuRI3Hjjjfj973/vdsxsNmPz5s14+OGHMXLkSFRWVmLOnDmYPn06CgsLAQB9+/ZFeXm5m+6VV17B008/jWnTprmVP/roo5g1a5ZjPyUlJUitUgtO0PVKawdPTQWqquzbVjzLtMT401ht3vOSqUcVjYxOi8ZffvROzTbRu9BqZHR6uA+xD2nXyOii1buycuAf6wAAY//5A3DPx459J7G4r+Br5663mDZlAdC0xIx9Zwc+/ONEGILtXXyis6ysPHL7XaDyi/TxB0AcKMNl7+zApr2VzkLJfucWExCNF92f33ZpT4pS3skwbdq0NhPpVtLT07F69Wq3sueffx7jxo3Dvn370K9fPxiNRmRmZrrFLF++HFdeeWWbCXhqamqbWD3Aj7jrleZm57a01LnvrUxLjIzGV17+6lFFI6PTgw/0LrQaGZ0evJPR6cEHeqddI6OLUu8SKw5gbP8uvmMUoHBvJeqtttD2h/37I7ffBSq/SB9/AOr3lrpPzhVlbP+uSDQalPGupqYG1dXVjp/GxkYNrWpLVVUVDAYDunTp4vX4pk2bUFRUhJtvvrnNsaeeegrdu3fHqFGj8Pjjj8NisQQkJ9XhE3S9Yjbbt3V1wLBh9r+opaV5L9MS40+TkNQ2J9lzq6LxVdZZjb/86J2abaJ3kedDNIwl9iH1fIgA7wzDh+PD48dRn5gMVLesKl1WDqTZn6xZrVasWvUlpkzJhclk8hrjWRYQDQDz0eP2p/rt+RlI7w4fc5aNOw04cigy+12g8ov08QcAv/sdcOc7AIDCh85DUoPZb79r018l+qo/DdD+WErs3gWGmhplvMvJyXHbnz9/PvLy8rznJElDQwPuv/9+zJw5E2k+2rdkyRIMGTIEp59+ulv5XXfdhTFjxqBr164oKCjAvHnzUFJSgsWLF3cqp0iAE3RCCCGEEJ1hMBiQFBcLxBkBa6N9G2f/Z6HVIBBvBJLiYmEyeY/xLAuIBgBMxjC4QaKVpDgjkpol+p1nf5Xpq340gJ+xZDCEyRXvFBcXo3fv3o79+Pj4TtVntVpx1VVXobm5GS+88ILXmPr6erzzzjt4+OGH2xy7++67Hf8/YsQIdO3aFZdddpnjqXo0wwk6IYQQQgghhOiY1NRUn0+5O4rVasUVV1yBkpISfP311z7r/eijj2A2m3Hdddf5rXPChAkAgD179nCCTnSAt8UiPMu0xMhoZPJRWSOj04MP9C60GhmdHryT0enBB3qnXSOjo3e+Y4LlgxZNINqUEgXesQ85F0LuiMZbjMoaGV2gxl8HaZ2c7969G9988027k+klS5Zg+vTp6NGjh996t2zZAgDIysoKWK6qwgm6XmkdoGlpQHW1+zHPMi0x/jStr77wRKYeVTQyOi0af/nRu+Dnp7JGRqcH72R0ergPsQ9p18jo6J3vmKD54DGBCHabXO8DFeXOj+MH+jz+yjqrCVR+0dCHfv0FeOyrzuWnskZGp9U7CWpra7Fnzx7HfklJCYqKitCtWzdkZ2fjsssuw+bNm7Fy5UrYbDZUVFQAALp164a4uDiHbs+ePfj222/x+eeftznH+vXrsWHDBpxzzjlIT0/Hxo0bcffdd2P69Ono169fp9ugOlzFXa80NTm3q1Y5972VaYmR0fjKy189qmhkdHrwgd6FViOj04N3Mjo9+EDvtGtkdPROe5s644O/eoLVpjVrIt879iHgm2/81xOMNkWDdxIUFhZi9OjRGD16NADgnnvuwejRo/HII49g//79+PTTT7F//36MGjUKWVlZjp9169xfP/faa6+hd+/eyM3NbXOO+Ph4vP/++5g0aRJycnLwyCOPYNasWXj33Xc7lXukwAm6Xqmvt2/NZmDqVOeq7t7KtMTIaLwhU48qGhmdHnygd6HVyOj04J2MTg8+0DvtGhkdvdPeJs0+1PuvJ6BtcjnfpZdGuHfsQwCAK6/yX08w2hQN3kkwadIkCCHa/Lz++usYMGCA12NCCEyaNMmtnoULF6K0tBQxMW2no2PGjMGGDRtw/Phx1NfXY+fOncjLy0NSko+3r0QZnKATQgghhBBCCCEKwAk6IYQQQgghhBCiAJyg65XWj5PExAA5Oc59b2VaYmQ0vvLyV48qGhmdHnygd6HVyOj04J2MTg8+0DvtGhkdvdPeps744K+eYLXplFMi3zv2IWDwyf7rCUabosE7ogRcxV2vJCfbtykpwI4d7sc8y7TE+NP4Wj1Zph5VNDI6LRp/+dG74OenskZGpwfvZHR6uA+xD2nXyOjone+YoPmQrEHTiTa53gcKC9tfxV1579iHAAD//a/7Ku4q+6Cad0QJ+CcUvWK12rcWC7B4sX3bimeZlhgZjTdk6lFFI6PTgw/0LrQaGZ0evJPR6cEHeqddI6Ojd9rbpNkHq/96Atoml/O9vjTCvWMfAgC89Y7/eoLRpmjwjigBJ+h6paHBuZ01y7nvrUxLjIzGV17+6lFFI6PTgw/0LrQaGZ0evJPR6cEHeqddI6Ojd9rb1Bkf/NUTrDb96Y7I9459CLjnbv/1BKNN0eAdUQJO0AkhhBBCCCGEEAXgBF0hBgwYAIPB0ObnjjvuAAAIIZCXl4fs7GwkJiZi0qRJ2MHvkhBCCCGEEEJIVMAJukJs3LgR5eXljp/Vq1cDAC6//HIAwNNPP41nnnkGixYtwsaNG5GZmYnzzz8fNTU1HT+Z0ejc5uY6972VaYmR0fjKy189qmhkdHrwgd6FViOj04N3Mjo9+EDvtGtkdPROe5s644O/eoLVpsmTI9879iHgnEn+6wlGm6LBO6IEXMVdIXr06OG2/+STT+LEE0/E2WefDSEEnnvuOTz44IOYMWMGAGDp0qXo1asX3nnnHdx2220dO1lSkn2bnAysWuV+zLNMS4w/ja/Vk2XqUUUjo9Oi8ZcfvQt+fiprZHR68E5Gp4f7EPuQdo2Mjt75jgmaD0kaNJ1ok+t94JNP2l/FXXnv2IcAAO+/776Ku8o+qOYdUQI+QVcUi8WCt956CzfddBMMBgNKSkpQUVGB3NxcR0x8fDzOPvtsrFu3zmc9jY2NqK6udvy0Pm1vMpthtVphrauD9dFH7Vur1XuZlhgJTStWa1OHzm3XWDuWr6cuEBqZ/LRoJPKjd51rkzI+0Luw+xDKsRRt3tGHzmick0J659kms7s3Qe93Lud74skI907PfchlTP3jmRD3oUj3zvm7kKiBQQghwp0EacsHH3yAmTNnYt++fcjOzsa6detwxhln4MCBA8jOznbE3Xrrrdi7dy9W+fiLWF5eHhYsWNCmfPHixcjIyAha/v5otAH3Fdj/Sv30uCbE89M20tA7QgIDxxIJF+x7vgm1N7wW0YHrdXzs1CY8tInXVJYjR47glltuQWlpKfr06RPudAgACKIkubm54qKLLnLsf//99wKAKCsrc4u75ZZbxJQpU3zW09DQIKqqqhw/xcXFAoAo+fFHYbFYhOXoUWFJTLRvLRbvZVpi/GiO15pF/7krRf+5K8W+Q5XieK3Z/lN+SBxP7WLfetk/XFkt3v94hThcWS2t8arrpKaxsdFrO+vq6sSKFStEXV2dtHdtNH78dPXucGW19DXp6HlaY/y2SYsmTN4p5wO9C6sPoRxL0ead3nxoPHLE5+8cv79fvJTtO1Tp6HvHa81R7V1H+9Dx8kPu3gS537mdL7VLRHun5z50uLLacR3LuvYKaR+KdO927dolAIjS0tKgzWtIx+B30BVk7969WLNmDZYtW+Yoy8zMBABUVFQgKyvLUX7o0CH06tXLZ13x8fGIj4937FdXVwMAYmNjYTKZgNhYoL7evjWZ0HLQvUxLjB+NqbUMwFn/+7170rPfAp4r8L2PWKDg2w5qvOg6oRnbvys+/ONEGLy1E4DJZJL311PjLcaHdyZTrJRGy3lcNe22SYtGxocgeKecD/QurD6EYyxFi3d68kHU1+Oyd4uxaX+1s1J/v5e8/T7x+jum9VyxUemdlj5kio11L7dZg9rv3M7X0LIfod7puw+5X0e3uoLchyLfO/fzkvDD76AryL///W/07NkTF154oaNs4MCByMzMdKzsDti/p7527VqcfvrpHT9J62A0mYCbb3a/KXiWaYnxo0k0GXFqvy4dz1sRCvdWot5q895OV2S8k9FFm0ZGR+98x9A7OZ0efKB32jUyOpMJ9Tff6j45DyCn9uuCRJPRey5R4J3mPuSvnmC16brrI9879iFg5jX+6wlGm6LBO6IG4X6ET9yx2WyiX79+Yu7cuW2OPfnkkyI9PV0sW7ZMbNu2TVx99dUiKytLVFdXS9dfWlqqzMdYGhsbxfsfrxDHa82irtEq9XO81txhjVadN83hmgbHx6bqGq1t2mSxWMSKFSuExWKR9qGjmrpGq9tHt4J1ns7ook2jen4qa1TOL5RjKdq8C6Um3Pm59pPDNQ0B/f3S2NgY1PYE0odQaVz9DsXv2fbOF2neBUOjen6tGrevLNXUh/3faqE+V2c0JSUlyswNiB0+QVeMNWvWYN++fbjpppvaHLvvvvswZ84czJ49G2PHjsWBAwfw5ZdfIjU1teMnamiwb+vrgVtusW9b8SzTEiOhMRgMiDcCSXGxzh+bFUmz/2jfetuPi9WkaaPTqplzp7uP3trp77g/jayfkayR0dE73zH0Tk6nBx/onXaNjK6+Hph9h2M3Kc7o//eSt98nPjQGgyH8PijXhxr81xPQNrmcb/YdEe4d+xAAYM49/usJRpuiwTuiBJygK0Zubi6EEDj55JPbHDMYDMjLy0N5eTkaGhqwdu1aDBs2TNuJWl+pYLUCS5Y4972VaYmR0fjKy1894dS8sbT9evydR8U2hUMjo6N3vmPonZxODz7QO+0aGR3v+9rb1Bkf/NUTrDa9sTTyvWMfAt552389wWhTNHhHlIATdEIIIYQQQgghRAE4QSeEEEIIIYQQQhSAE3S90vrqtfh4YP585763Mi0xMhpfefmrJ5yaeQ+0X4+/86jYpnBoZHT0zncMvZPT6cEHeqddI6PjfV97mzrjg796gtWmeQ9EvnfsQ8C9f/VfTzDaFA3eETUI9yp1JLSotIp7JK6iGerVZb3BVdxDr1E9P5U1KufHVdwjQxPu/FS472vVqJ6fCn5zFXd1zsVV3MOj4Sru6sEn6HrFbLZv6+qAKVPs21Y8y7TEyGi8IVNPODWXXNJ+Pf7Oo2KbwqGR0dE73zH0Tk6nBx/onXaNjI73fe1t0uyD2X89AW2Ty/kuuSTCvWMfAgBceaX/eoLRpmjwjigBJ+h6xWZzbr/80rnvrUxLjIzGV17+6gmn5quv2q/H33lUbFM4NDI6euc7ht7J6fTgA73TrpHR8b6vvU2d8cFfPcFq01dfRb537EPAN//xX08w2hQN3hEl4ASdEEIIIYQQQghRAE7QCSGEEEIIIYQQBeAEXa8kJDi3r77q3PdWpiVGRuMrL3/1hFOz6F/t1+PvPCq2KRwaGR298x1D7+R0evCB3mnXyOh439feps744K+eYLVp0b8i3zv2IeCZZ/3XE4w2RYN3RA3CvUodCS1cxT2yVpf1BldxD71G9fxU1qicH1dxjwxNuPNT4b6vVaN6fir4zVXc1TkXV3EPj6ajq7ivXbtWXHTRRSIrK0sAEMuXL3er87777hPDhg0TSUlJIisrS1x77bXiwIEDbnWcffbZAoDbz5VXXukWc+zYMfGHP/xBpKWlibS0NPGHP/xBVFZWSrcvkuETdL3SuoJjbS0wdKh924pnmZYYGY03ZOoJp2bs2Pbr8XceFdsUDo2Mjt75jqF3cjo9+EDvtGtkdLzva2+TZh+cK0ybLTaYj1XBPGKUfWtpgtnShEYbHP9vtjS1jemQptp5vvET3TRtdC71CiEU9C60/UHU1Pj0uz3v2ivTrnEufFY/abJ/P8PsnbLjT4K6ujqMHDkSixYtanPMbDZj8+bNePjhh7F582YsW7YMu3btwvTp09vEzpo1C+Xl5Y6fl19+2e34zJkzUVRUhPz8fOTn56OoqAjXXnttp3KPFGLDnQAJE83Nzm1xsXPfW5mWGBmNr7z81RNOzc6dwAXt1OPvPCq2KRwaGR298x1D7+R0evCB3mnXyOh439feps740MLYx9bY/+eCx4Gnv3MJisV9BV+76zxjZDXPrXeeb0qeh8aLrqXesf274sOZQ2FQzbsQ9QdRXIzLlhZh0/6WP3C08Rvw5Z0b/q6TpAYFax17Z533QPtt9NEmjj85pk2bhmnTpnk9lp6ejtWrV7uVPf/88xg3bhz27duHfv36OcqTkpKQmZnptZ6ffvoJ+fn52LBhA8aPHw8AePXVVzFx4kT8/PPPGDx4cKfaoDp8gk4IIYQQQpQg0RSDsft3hDsNvxTurUS9tXMTnUim3hTvnJwrytj+XZFoMoY7Dd1TVVUFg8GALl26uJW//fbbyMjIwNChQ3HvvfeipqbGcWz9+vVIT093TM4BYMKECUhPT8e6detClXrY4BN0QgghhBCiBAaDAR++PRf1h48BaalAdQ2QnQWUlQNpqbBarVi16ktMmZILk8lkF3nEdERj/m0/xv6/HwAAhf9vJpL2/WavA2irq66Buf9AjP3z22FwRl0K7xqPpP59nP7Du3du1wjwf506oDnrnMmY+JT9KXrrdUzs3gUGgyEclkQkNTU1qK52/tElPj4e8fHxnaqzoaEB999/P2bOnIm0tDRH+TXXXIOBAwciMzMT27dvx7x587B161bH0/eKigr07NmzTX09e/ZERUVFp3KKBDhB1yuJifZtUhKQn2/ftuJZpiVGRuMNmXrCqVmxAvjW5l7Wni4YPvj6g73q3nXUh2jtQ/ROHR+iYSyxD2nXyOhUue+rppHRdcIHQ34+krqkArGxQJdU4LNP7NvYWFgNAvFGICkuFiZTyz9jPWI6pklxnvqj953nBdrquqQCH77n7A9Jicp5F45/DyWlpyDJ1X/48M4jxu916pDG+aTccR1bJ+eqeafo+MvJyXHbnz9/PvLy8nzn5Qer1YqrrroKzc3NeOGFF9yOzZo1y/H/w4YNw6BBgzB27Fhs3rwZY8aMAQCvf1wRQujijy6coOuV1htdbCwwZUrbY65lWmJkNL7y8ldPODXnnQd8u0peFwwfLE0d12g5TzA1Mrpo7UP0Th0fomEssQ9p18joVLnvq6aR0UWKD673gfPOc/77yJfGtT/o2TuVffC8jqp5p+j4Ky4uRu/evR37nXl6brVaccUVV6CkpARff/2129Nzb4wZMwYmkwm7d+/GmDFjkJmZiYMHD7aJO3z4MHr16qU5r0iB30HXK63f86iuBtLS7NtWPMu0xMhovCFTTzg1mVnt1+PvPCq2KRwaGR298x1D7+R0evCB3mnXyOh439fepojxwfm9V2Rm+de49ofqGv16p7IPntdRNe8UHX+pqalIS0tz/GidoLdOznfv3o01a9age/fufjU7duyA1WpFVpa9X02cOBFVVVUoKChwxPzwww+oqqrC6aefrimvSIJP0Ilzst5emZYYGY1MPippajW0KRp9CIRGRkfvfMfQOzmdHnygd9o1Mjre933HRJsP3q61J54xevVOZR+0jFlvMSprZHRa+5AfamtrsWfPHsd+SUkJioqK0K1bN2RnZ+Oyyy7D5s2bsXLlSthsNsd3xrt164a4uDj88ssvePvtt3HBBRcgIyMDxcXF+Mtf/oLRo0fjjDPOAAAMGTIEU6dOxaxZsxyvX7v11ltx0UUXRf0K7gAn6IQQQgghhBBCJCgsLMQ555zj2L/nnnsAANdffz3y8vLw6aefAgBGjRrlpvvmm28wadIkxMXF4auvvsI///lP1NbWom/fvrjwwgsxf/58GI3OtQTefvtt3HnnncjNzQUATJ8+3eu716MRTtAJIYQQQgghhPhl0qRJEEL4PN7eMQDo27cv1q5d224MYH/i/tZbb3U4v2ggJtwJkDDRuoJjcjKwfbt924pnmZYYGY03ZOoJp6ZgY/v1+DuPim0Kh0ZGR+98x9A7OZ0efKB32jUyOt73tbcpYnxwWdG6YKN/jWt/SE7Sr3cq++B5HVXzTuXxR5SAE3S9EhPj3Pbt69z3VqYlRkbjKy9/9YRT06dP+/X4O4+KbQqHRkZH73zH0Ds5nR58oHfaNTI63ve1tynSfADs19qfxrU/6Nk7lX3wvI6qeafy+CNKwCukV2pr7duaGiA93X3RCM8yLTEyGm/I1BNOTXZW27L2dNHqQ2c1Mjp65zuG3snp9OADvdOukdHxvq+9TRHjQ62zLDvLv8a1P9TU6tc7lX3wvI6qeafy+CNKwAk6IYQQQgghhBCiAJygE0IIIYQQQgghCsAJOiGEEEIIIYQQogCcoOuVlBT7NjUVqKqyb1vxLNMSI6Pxhkw94dSUlbdfj7/zqNimcGhkdPTOdwy9k9PpwQd6p10jo+N9X3ubIsaHFGdZWbl/jWt/SE3Rr3cq++B5HVXzTuXxR5SAE3S90tzs3JaWOve9lWmJkdH4ystfPeHU7N/ffj3+zqNim8KhkdHRO98x9E5Opwcf6J12jYyO933tbYo0HwD7tfance0PevZOZR88r6Nq3qk8/ogScIKuV8xm+7auDhg2zL5txbNMS4yMxhsy9YRTM+609uvxdx4V2xQOjYyO3vmOoXdyOj34QO+0a2R0vO9rb1PE+GB2lo07zb/GtT/UmfXrnco+eF5H1bxTefwRJeAEnRBCCCGEEEIIUQBO0AkhhBBCCCGEEAXgBJ14XyzCs0xLjIxGJh+VNCka2hSNPgRCI6Ojd75j6J2cTg8+0DvtGhkd7/u+Y6LNB2/X2hPPGL16p7IPWsastxiVNTI6rX2IhJ3YcCdAwkTrAE1LA6qr3Y95lmmJkdF4Q6aecGoqyoFHVsnrguGDpanjGi3nCaZGRhetfYjeqeNDNIwl9iHtGhmdKvd91TQyukjxwfU+UFEOxLXzT2PP/pCWql/vVPbB8zqq5p3K448oAZ+g65WmJud21SrnvrcyLTEyGl95+asnnJo1a9qvx995VGxTODQyOnrnO4beyen04AO9066R0fG+r71NkeYDYL/W/jSu/UHP3qnsg+d1VM07lccfUQJO0PVKfb19azYDU6c6V3X3VqYlRkbjDZl6wqm59NL26/F3HhXbFA6NjI7e+Y6hd3I6PfhA77RrZHS872tvU8T4UO8su/RS/xrX/mCu1693KvvgeR1V807l8UeUgBN0QgghhBBCCCFEAThBJ4QQQgghhBBCFIATdL0SE+Pc5uQ4972VaYmR0fjKy1894dScckr79fg7j4ptCodGRkfvfMfQOzmdHnygd9o1Mjre97W3KdJ8AOzX2p/GtT/o2TuVffC8jqp5p/L4I0rAVdz1SnKyfZuSAuzY4X7Ms0xLjIzGGzL1hFNTWOi+mq8/XTB88LXytOreddSHaO1D9E4dH6JhLLEPadfI6FS576umkdFFig+u94HCwvZXcffsDynJ+vVOZR88r6Nq3qk8/ogS8E8oesVqtW8tFmDxYvu2Fc8yLTEyGm/I1BNOzetL26/H33lUbFM4NDI6euc7ht7J6fTgA73TrpHR8b6vvU0R44PVWfb6Uv8a1/5gserXO5V98LyOqnmn8vgjSsAJul5paHBuZ81y7nsr0xIjo/GVl796wqn50x3t1+PvPCq2KRwaGR298x1D7+R0evCB3mnXyOh439fepkjzAbBfa38a1/6gZ+9U9sHzOqrmncrjjygBJ+iEEEIIIYQQQogC8DvohBBCCCGEdBCz1QaY4gGLDa3fZbdam9BoA8yWJpiEwX7MI8azLCAaLzGB0Phqk9mUEEqrCdEVnKDrFaPRuc3Nde57K9MSI6PxlZe/esKpmTy5/Xr8nUfFNoVDI6Ojd75j6J2cTg8+0DvtGhkd7/va2xRpPgD2a+1P49Ifxv7zB+Cej4F/rPMIjMV9BV87d73FtCkLgMZbTEA0XnR/ftv5/6r1Ic/rqHK/U807ogScoOuVpCT7NjkZWLXK/ZhnmZYYGY03ZOoJp+aTT9xX8/WnC4YPvlaeVt27jvoQrX2I3qnjQzSMJfYh7RoZnSr3fdU0MrpI8cH1PvDJJ+2v4p6cjMTPV2LsS+tRuLey/fp1wtj+XZHYJVWtPuR5HVXsd53RyOi0ekeUgN9B1yutKzg2NgJ5efZtK55lWmJkNN6QqSecmscXtl+Pv/Oo2KZwaGR09M53DL2T0+nBB3qnXSOj431fe5sixgeXFa0fX+hXY1iwAB/eOAbFj05B8YPnoDh+k3376BQUPzoFWx8+F0+Pa8LWh8/1GeNZFhCNN10ANP7y+/CPE2GwWNTqQ57XUcl+p+j4I2ogiK4oLS0VAERpcbG9oKpKCMC+bcWzTEuMhMZisYgVK1YIi8UiXa8WjVedRk2dKV70n7tS9J+7UtQ1Wv3nFwQf6hqtjhyO15ojxrsO+xClfYjeqeNDKMdStHmnJx9UuO9Hqneq+NCepu7wMef1NcXTuwjtQ8drzT6vI71rX1NSUmKfG5SWCqIGfIJOCCGEEEIIIYQoACfohBBCCCGEEEL88u233+Liiy9GdnY2DAYDVqxY4ThmtVoxd+5cDB8+HMnJycjOzsZ1112HsrIyR8yxY8fw5z//GYMHD0ZSUhL69euHO++8E1VVVW7nGTBgAAwGg9vP/fffH6pmhhVO0PWKyeTc3nyzc99bmZYYGY2vvPzVE07Ndde3X4+/86jYpnBoZHT0zncMvZPT6cEHeqddI6PjfV97myLNB8B+reld5Pchz+uosg+qeSdBXV0dRo4ciUWLFrU5ZjabsXnzZjz88MPYvHkzli1bhl27dmH69OmOmLKyMpSVleEf//gHtm3bhtdffx35+fm4+eab29T36KOPory83PHz0EMPdSr3iCHcn7EnocXxHXQFvmfi9fs8QdAE8lyu31mta7QG7Tzt4fN7swE+T2d00aZRPT+VNSrnF8qxFG3ehVIT7vxUuO9r1aienwqa9q6vCvmFW6N6fl6/g+5lnIYjt1CeqzOaznwHHYBYvnx5uzEFBQUCgNi7d6/PmA8++EDExcUJq9V57fr37y+effbZDucUDfAJul5paLBv6+uBW26xb1vxLNMSI6Pxhkw94dTMvqP9evydR8U2hUMjo6N3vmPonZxODz7QO+0aGR3v+9rbFDE+NDjLZt9B76KhD3leR5V9UMi7mpoaVFdXO34aA7Tae1VVFQwGA7p06dJuTFpaGmJj3V9z+NRTT6F79+4YNWoUHn/8cVgsFh81RBecoOsVq9W5XbLEue+tTEuMjMZXXv7qCafmjaXt1+PvPCq2KRwaGR298x1D7+R0evCB3mnXyOh439fepkjzAbBfa3oX+X3I8zqq7INC3uXk5CA9Pd3x88QTT/jOSZKGhgbcf//9mDlzJtLS0rzGHD16FH/7299w2223uZXfddddeO+99/DNN9/gT3/6E5577jnMnj270zlFArH+QwghhBBCCCGERCvFxcXo3bu3Yz8+Pr5T9VmtVlx11VVobm7GCy+84DWmuroaF154IXJycjB//ny3Y3fffbfj/0eMGIGuXbvisssuczxVj2Y4QSeEEEIIIYQQHZOamurzKXdHsVqtuOKKK1BSUoKvv/7aa701NTWYOnUqUlJSsHz5cpj8LF43YcIEAMCePXuifoLOj7grxoEDB/CHP/wB3bt3R1JSEkaNGoVNmzY5jgshkJeXh+zsbCQmJmLSpEnYsWNHx0/U+lex+Hhg/nznvrcyLTEyGl95+asnnJp5D7Rfj7/zqNimcGhkdPTOdwy9k9PpwQd6p10jo+N9X3ubIs0HwH6t6V3k9yHP66iyD6p5FwBaJ+e7d+/GmjVrvE6mq6urkZubi7i4OHz66adISEjwW++WLVsAAFlZWQHPWTnCvUodcXLs2DHRv39/ccMNN4gffvhBlJSUiDVr1og9e/Y4Yp588kmRmpoqPv74Y7Ft2zZx5ZVXiqysLFFdXS11Dq7iHvmr+XIV99BrVM9PZY3K+XEV98jQhDs/Fe77WjWq56eChqu4q3MuruIeHk1HV3GvqakRW7ZsEVu2bBEAxDPPPCO2bNki9u7dK6xWq5g+fbro06ePKCoqEuXl5Y6fxsZGIYQQ1dXVYvz48WL48OFiz549bjFNTU1CCCHWrVvnqPfXX38V77//vsjOzhbTp0+Xbl8kwyfoCvHUU0+hb9+++Pe//41x48ZhwIABmDx5Mk488UQA9qfnzz33HB588EHMmDEDw4YNw9KlS2E2m/HOO+907GRms31bVwdMmWLftuJZpiVGRuMNmXrCqbnkkvbr8XceFdsUDo2Mjt75jqF3cjo9+EDvtGtkdLzva29TxPhgdpZdcgm9i4Y+5HkdVfZBNe8kKCwsxOjRozF69GgAwD333IPRo0fjkUcewf79+/Hpp59i//79GDVqFLKyshw/69atAwBs2rQJP/zwA7Zt24aTTjrJLaa0tBQAEB8fj/fffx+TJk1CTk4OHnnkEcyaNQvvvvtup3KPFPgddIX49NNPMWXKFFx++eVYu3YtevfujdmzZ2PWrFkAgJKSElRUVCA3N9ehiY+Px9lnn41169a1Wf2wXWw25/bLL5373sq0xMhofOXlr55war76Chg5272sPV0wfDAFuE3h0MjoorUP0Tt1fIiGscQ+pF0jo1Plvq+aRkYXaT4A9mtN7yK/D3leR5V9UM07CSZNmgQhhM/j7R2T0QPAmDFjsGHDBk35RQOcoCvEr7/+ihdffBH33HMPHnjgARQUFODOO+9EfHw8rrvuOlRUVAAAevXq5abr1asX9u7d67XOxsZGt/cY1tTUAACamppgtVqBpiYgMdG+bX3tgmeZlhgJjbWl3Or6ugc/9WjRuMZbO9BGbxprQqLjtFarFVZ/+QXBB9c4q7VJuk3h9q7DPkRpH6J36vgQyrEUbd7pyQcV7vuB9s6WlIzCX4/ikO04ehptGJuUDGMU96H2NNamJuf1TWjZV6DfqeJd5Pjg+zrSuw74QJTAIPz9CYOEjLi4OIwdO9bxERAAuPPOO7Fx40asX78e69atwxlnnIGysjK3BRJmzZqF0tJS5Ofnt6kzLy8PCxYsaFO+ePFiZGRkBKchUUyjDbivwP53rafHNSHeqM8cCIkGOJaIDNHWT7YeNWDZbzE4bjE4yrrECcwY0IyR3fX3T8Jou756hddRO0eOHMEtt9yC0tJS9OnTJ9zpEICLxKlEv379xM033+xW9sILL4js7GwhhBC//PKLACA2b97sFjN9+nRx3XXXea2zoaFBVFVVOX6Ki4sFAFHy88/CYrEIS22tsCxebN9aLN7LtMRIaOrq6sSKFStEXV2ddL1aNF51GjXHX1nitqiU3/yC4IPrQiiHK6sjxrsO+xClfYjeqeNDKMdStHmnJx9UuO8HyrvPtpSKAXNXiv5zP3O0qf/clWLA3M/EgLkrxWdbSqOyD7WnOX6synl9X1miTL9TxbtI8eFwZbXP60jv2tfs2rVLmQWkiR1O0BXi6quvFmeeeaZb2Zw5c8TEiROFEEI0NzeLzMxM8dRTTzmONzY2ivT0dPHSSy9JnYOruEf+ar5cxT30GtXzU1mjcn5cxT0yNOHOT4X7vlaNq66+oVFMWLjGbWLuPklfKSYsXCOabM1KtynQGq7irs65OqPhKu6hW8WdBB+u4q4Qd999NzZs2ICFCxdiz549eOedd/DKK6/gjjvuAAAYDAbMmTMHCxcuxPLly7F9+3bccMMNSEpKwsyZMzt2stYVHGtrgaFD7dtWPMu0xMhovCFTTzg1Y8e2X4+/86jYpnBoZHT0zncMvZPT6cEHeqddI6OLovt+4d5KlFc1+KxKACivakBBybHAtElRH9pqXFa0HjtWnX4XEd4p6oPndVTZB9W8I0oQG+4EiJPTTjsNy5cvx7x58/Doo49i4MCBeO6553DNNdc4Yu677z7U19dj9uzZqKysxPjx4/Hll18iNTW1YydrbnZui4ud+97KtMTIaHzl5a+ecGp27gQuaKcef+dRsU3h0Mjo6J3vGHonp9ODD/ROu0ZGF0X3/UM1jW3KvHGopgFAWufbpKgP7eayc6c6/S6SvFPNB8/rqLIPqnlHlIATdMW46KKLcNFFF/k8bjAYkJeXh7y8vNAlRbxittgAiw0wxdu3liZYrU1otAFmSxNMwtDmOAD/Gi8xrvvmmCa3HEwm7/V6Ow+XhCSERANCCNS3c78DEJj7scUGsykhjC0NHCaj3Icme6ZGR3sJISRS4QSdEI2MfWyN/X/u+Rj4xzqXI7G4r+Br526b4xIabzFe6pn41NoOaQamGnHBBZylE0IiFyEELnvzR2ySuEcG5H7857cDlXpYOXdwD8TFxsDS5P3pmQFAZnoC+nRNxBNf/IyT+OYlQggJC/wOul5JbHmva1ISkJ9v37biWaYlxo/G1izwQ8kxbDpiwA8lx2BrFvL1eBJCTeKnKzC2XxffMYpTUmNAvdXmLAiX3zI6LZpwtonehVYjo9ODDzr0rt5qw6b91b7rCxJj+3dFoskYUd412ZrR3PL7NS42Bk/8zzAA9sm4K6378y/OwTOrd+G1dXvxzi8u/0SMsj7kHuN8zz1WrOD4i4b7kOd1VNkH1bwjSsAn6HolNta5nTKl7THXMi0x7Wjyt5djwWfFLYvVGPHG7kJkpSdg/sU5mDosy3893toSIo1h6lR8KIT7JNcFq9WKVau+xJQpuTCZTO3Xp1FjtjRh7GNfAQDWzz0b6cn+P45otticT/xdCaF3fvtQIDSByk9ljYxOD97J6PxpLE1tNYHKT2WNjE71PtRC4UPnISnO+wuPA30/TjQZYTAYIsa7o7WN+NM7W3D6CV3Rr+Xw70/ti+T4WJffwXYyXX4HJ8fH4qfyakztUek4bosxIiY3195+2fwU8cGvxvU+cN55zn8fBSs3GV2keNcZjYxOqw+e11FlH1TzjigBn6DrlZoa+7a6GkhLs29b8SzTEuNDkz9qMm5/a3OblWQrqhpw+1ubkV/wq/96PJE5dwA1hpoaJMXF2n8azEjK6GbftpTFG9Hucb8abzEe+60kxRklNd7/ARtq79rtQ4HQhLNN9C60GhmdHnzQq3ct+LpHBux+7HLcMTmNEO/W7jqM9b8excv//Q21Lh9Xn9ovGd89OQPvXjMc/7xqFN69Zji+e3IGpvZLBgCcNagHPp09AX1TnJo3vtmJK6//X2z7+YB8mxTxwb+mxlmWmcXxFw33Ic/rqLIPqnlHlIBP0Ilzst5emZYYj31bs8CC06+Ft29AC9g/Yrdgza84v7YObtNJb+fWkm8wNDI6LRpvMdGmkdHRO98x9E5Opwcf9OqdvzpkY4LhgwLezRjTB6XH6nH+kAzsLvzWLcRYXY2J/bs4/7Hu8Q921yflVlszXt6wHxXZQ/BjeS2GD+5Afgr40CFNLcdfSDUyOi0ab9dRZR9U8o4oQUy4EyD6oaC0CuVpPXweFwDKqxtR0Gdo6JIihBBCooDGJhteWFeKRqPz2ctd5w3CoJ4p7aj8YzLGYNn1o/DHDR/iylGZjvJ9lfWojUtsR0kIIUQLnKCTkHGo1iIXl9I1yJkQQggh0cWtb2zC0//5DQsm3xbwurPT4nH/2qWIjbE/WRdC4M5PfsakWa/gh31VAT8fIYToGU7Q9UrrCo7JycD27fZtK55lWmK8aHpmpEml1vP5/23/3J7I5BsMjYxOiyacbaJ36mtkdHrwTkanBx/06p1D287vskC0KYK8u+nMgeiWZMKUe28I+jU6WN2I4402mLt0w8A+3eXOo/Fcwde4rGhdsJHjLxruQ57XUWUfVPOOKAG/g65XYmKc2759nfveyrTEeNGMOyEDWalxqKixeP0eeus7WMeOOan9c3tri798g6GR0WnR+MvP5n0F+YBrtOQmq5HRBcO7aNDI6PTgnYzOn0a1cRFJ3oW7Ta5areeR0SnsnRACR+qs6NESc/bJPfDtfecgxVIf9GuUmZ6AL+f8DsW/VKBnuvNj7usOGjDoYC1y+nRVvw95i+nTh+MvGu5DntdRZR9U844oAa+QXqmttW9raoD0dPdFIzzLtMR40RjrajH/jfkAfL+D9fLhPfA/dy/Fvn2HfJ/bE5l8g6GR0WnRhLNN9E59jYxOD97J6PTgg169c2jb+V0WiDYp6l1dYxP+9O4WzHjhexzv1dsRk2KpD1kfiquvw6ghfRxlvxyuw4e/xuDiF9aj5Eid+n3IEVPrLMvO4viLhvuQ53VU2QfVvCNKwAk6CSlTd63HizOGIDPd/d3dmekJ+NfMMfhi51FszzwJr20sC1OGhBBCiNpYbc34cf9xlFc3orB3TrjTAQDEx8ZgWDeBSSdnYGAGP0JLCCFa4UfcSciZekoGzh87EOv3HMKX//0BuWeNx8STesIYY8DobrH4f7cswP33PRbuNAkhhBAl6ZIUh5f/MBbmyiqMfaIg3OkAAPp0TcTNg5sxOXeko6w+Nh7XvrEV1555AqaPzG7z6TlCCCFt4RN0EhaMMQaMH9gNp2YIjB/YDcaWlWGz0uLxxKp/ISHW2TXfHTkFVQ1N4UqVEEIICSu2ZoFn1+zBT8edU9yc7DSM7Zsexqy8E+/y+/vNMRegcH81ns7/GY1NzWHMihBCIgc+QdcrKS3vRU1NBaqq7NtWPMu0xMhovOER89GuKsyb+me8+saP+Pyus2CU0Gg5jyaNjC5APrjtW30sbBVojZbcZDUyumB4Fw0aGZ0evJPR+dOoNi4iybtwt8mhbed3WSDapIh3b677DS+s/RVJxhjcbLaiR7rJr0bLeaQ1kj5c+/kSWLYewUk9U5BgMgKxds1BYUKvYObXEU28y7vcy8qV8U7p8ae6D57XUWUfVPOOKAGfoOuV5mbntrTUue+tTEuMjMZXXi4xg3smo3eyEZeMzLL/cpfQaDmPJo2MLkA+RJ1GRkfvfMfQOzmdHnzQq3euWq3nkdEp4t3V4/th/MCu+P3AZnRJMklptJxHWiPpQ2JFGf509gmYOizLUfafDT/jzKe/wdP5O4OXn9Y27d+vjHdKjz/VffC8jir7oJp3RAk4QdcrZrN9W1cHDBtm37biWaYlRkbjDY+Y4V1i8fnjl+HP4zIdIQ02+wI5HcrXz3k0aWR0AfIh6jQyOnrnO4beyen04INevXNo2/ldFog2hdG7zbvKHfvxsUa8eeNYjO0h2tVEQh/6+u+vwWoTsPj4yLutphbrp12NTwpKsP6Xo7DV1Aa5TWZn2bjTlPZOmfGnug+e11ExH2zDR2B98QF8UnQA64sPwDZ8hDreESXgR9yJ8qQ31gEG+/fumpsFlu6KwceHNuFf15yKHqnxYc6OEEIICRxCCDz62Q78+/vf8OSIXFzVUm4wRMcSawvWvIRznp6LMYN7O8rKqxrw86FjaLI149FPt6N85hPAJz8DALJS4zD/5ImYGq6ECQkg+TuPYMEfl6D87W2Osqw/LsH8nUcwdVxaGDMjKsEJOokofjlSh1+qDUBtFQ5WN3CCTgghJOKwNQvsrjLgsx/LkdUlGeMGdnOssWIwGJCRYv/ddji5a/iSDBIGAOec2A1IMsFqtQIAnlm9Gyu2lnuNr6ix4PZLH8CLnMCQCCd/ezluX/YTRGqGW3lFanfcvuwnvJiU6Pw6CNE1nKAT74tFeJZpiZHRyOTjsj+oZwr+MsKG3kNGYVjvdCmNlvNIa2R0QfAhKjQyOnrnO4beyen04INevfNXh2xMMHxoR5O/vRx5n+5ARbURKLY/RctKT8AjkwdgWkvM7WefiImZCRjzwtXtn8fbuSKsDwkB9Erz/cd2AcAAgQVrfsX5YwfKn0tLm1IiyzspncoaGZ0WjbfrGGYfbM0CCz4rhgAcnwptRRhiYACw4LNinJ+T6U0e2j5Ewg4n6HqldYCmpQHV1e7HPMu0xMhovCFRT69EIDfHuf5raVMsXnt7PeYmJiMhgOfxq5HRBcMHi49XzgVaoyU3WY2MLoh9KKI1Mjo9eCej86dRbVxEknfBzE9G44ht53eZv/PI6AKsyd9ejtvf2gyPb5KjvKoBty/biRe++xkXpKUhBsCYIX3U8TuI3hkMwFmDMvDyf3/zWZUwxKC8uhEFJccwtp+Xp+idaZPrfaCiHIhr55/GinkXlPwisA+1wfM6KuBD4d5KlFc1+KxKwH4f8NrHQ+kdUQIuEqdXmpqc21WrnPveyrTEyGh85eWvHheamwX+9PYm/Pv73zB/xbagnUdzm0LkQ8RpZHT0zncMvZPT6cEHvXrnqtV6HhldADW2/Hws+HRHm8m5Kw98sBk2i1V7myK0Dx2qafR9brc4HxOcQLVpzZqI8y7g+UVoH3LD8zqG2Yc6K7DnkNzCbF77eCi9k+Dbb7/FxRdfjOzsbBgMBqxYscJxzGq1Yu7cuRg+fDiSk5ORnZ2N6667DmVlZW51NDY24s9//jMyMjKQnJyM6dOnY//+/W4xlZWVuPbaa5Geno709HRce+21OH78eKdyjxQ4Qdcr9fX2rdkMTJ3qXNXdW5mWGBmNN2TqcSEmxoB7f9cPJx4txZ0TsoN2Hs1tCpEPEaeR0dE73zH0Tk6nBx/06p1D287vskC0KYCaglvvQ3l1+xPR401Awc/l2tsUoX2op+R6MrsP1uDP723FL54PATvVpnpn2aWXRpx3Ac8vQvuQG57XMYw+vLFhHx7ZZMT3vxz1XY8LPVMT/J9HJj+t3klQV1eHkSNHYtGiRV5Oa8bmzZvx8MMPY/PmzVi2bBl27dqF6dOnu8XNmTMHy5cvx3vvvYfvvvsOtbW1uOiii2Cz2RwxM2fORFFREfLz85Gfn4+ioiJce+21nco9UuBH3EnEc9bArvhyyR0w/u9MR9lPPQbgFCEQHWveEkIIiXQOpcgt+Hao1hLkTNRjbP+uyEpPQEVVg9dPGBhEMzLTE/HDr8ewcW8lYvrytztRk0PJXZHY2ITWb3oPzEhCkzCgut6CzPQEHPTVxwFkpidg3MBuaLZ17gl3sJk2bRqmTZvm9Vh6ejpWr17tVvb8889j3Lhx2LdvH/r164eqqiosWbIEb775Js477zwAwFtvvYW+fftizZo1mDJlCn766Sfk5+djw4YNGD9+PADg1VdfxcSJE/Hzzz9j8ODBwW1kmOETdBIVGIXzfao/ltfgkuuewexlP6HBamtHRQghhISGnrWVcnEpcUHORD2MMQbMvzgHANr8Yd3Q8t/5552ABZcMw7Xj+2K8y/vgt+yrxI3vb8fXJ4wNVbqEeOWJr0swcfbr+PjHg46yM07ojnuHN+HNm05DXmsfd/k3q+v+/ItzYIyJvj8+VVVVwWAwoEuXLgCATZs2wWq1Ijc31xGTnZ2NYcOGYd26dQCA9evXIz093TE5B4AJEyYgPT3dERPNcIKuV2JinNucHOe+tzItMTIaX3n5q8eP5tdjDRAxMbAKIM7oQxeA80jpwuiD0hoZHb3zHUPv5HR68EGv3rlqtZ5HRhdAzbjUZmSl+p58GwBkmSsxrn9X7W2K4D40dVgWXvzDGGR6eJSZFo8XC9/E1JyeyMlOwyMXDUEXl0/Ev1uwD9/8UomVEy7qfJtOOSUivQtofhHchxx4XscgtWl/tQW2nKGOmOz0BNhijNh+0Pl985gYA/qm2F+fOHVYFl68LAeZDdVu9WTWV+HFy3J8v2ItRN7V1NSgurra8dPYKLc2RHs0NDTg/vvvx8yZM5GWZl/8rqKiAnFxceja1f1TRb169UJFRYUjpmfPnm3q69mzpyMmmuFH3PVKcrJ9m5IC7NjhfsyzTEuMjMYbMvX40Vw68UQM6NMdJ/RIRoyvv0QG4DxSumD44Gvl6UBrtOQmq5HRhbEPKa2R0enBOxmdP41q4yKSvAtmfjIaR2w7v8v8nUdGFyBNSYMBA3dsx3wfq7i3/qaaf+tkGFtXplfJ7xB5N3VYFs7PyURByTEcqmlAz1T7R36ND5znU3P7pJPQNTkOU4aebq8fwCERi7vvXoLLd1fhklHJ7efneh8oLGx/FXeFvQtYfhHehwC0vY5BaNOf392ClT+W4d/Lvsakln73PxNPwMScbJzcy/erzKaOHYjzxwxo28fbe3IeIu9ycnLc9ufPn4+8vDzf5/CD1WrFVVddhebmZrzwwgt+44UQMLi8gs5gaOuJZ0y0IvHnaRKVWFtWibVYgMWL7dtWPMu0xMhovCFTj4Rm1KqPkBbj/CfQ81//gs/2xsDWLAJ3HhldmH1QViOjo3e+Y+idnE4PPujVO4e2nd9lgWhTJzVWWzPmLduG3GfXomjRUkw9ubv9KbHHe78z0xPw4lUjMHXD/+m+DxmbrJj4zXJcktMDE0/sDmOTtV3NwIxkzJt8IsZ8+bEj5uOCvfh+z1G8sa7E9z/mHblYnWWvL41o73gfasHzOgagTZ6vSOueHAchgKJPvnbEpMUInPzZ+37PY3xtCSb2TcUlo3pjYt9UGF9booR3xcXFqKqqcvzMmzfPd05+sFqtuOKKK1BSUoLVq1c7np4DQGZmJiwWCyor3b/2c+jQIfTq1csRc/DgQXhy+PBhR0xUI4iuKC0tFQBEaXGxvaCqSgjAvm3Fs0xLjITGYrGIFStWCIvFIl2vFs2uimox4P6Vov/clWLNjjLpfNucS0ubguBDXaNV9J9rb8/xWnPQNNI+RJB3WjVB84HehdUHreOC3oXXB9frVnf4mHo+uBxvbm4Wt79VKAbMXSmWnDrdoalvaBR/X/qJ+Lhwr1i354hosjWzD0m2SUZzoPSQePaMq8XnP/zi0Hy0bIW4bskG8e4Pe0WDtcmhqTt8zNmfTPG69y5S+9DxWrPP69gZHyzHKsWVL68TA+5fKV5916kpO24Wv/1WERXelZSU2OcGpaWiowAQy5cvdyuzWCzi0ksvFUOHDhWHDh1qozl+/LgwmUzi/fffd5SVlZWJmJgYkZ+fL4QQori4WAAQP/zwgyNmw4YNAoDYuXNnh/OMNPgRdxL1DOqVimcuG47Pvt+K3w3KCHc6hBBCopxmGBAD+0c0n/z9CPxheA+c/tSnjuPGGAMGpQtcMCILJpMpfIlGKdlp8Zjz/bvAKS85ynZUGrB21xHsKKvB70/tE8bsiOocrG5A6zNakzEG8bFGGACU1Dg/jZGVnggYrF710U5tbS327Nnj2C8pKUFRURG6deuG7OxsXHbZZdi8eTNWrlwJm83m+M54t27dEBcXh/T0dNx88834y1/+gu7du6Nbt2649957MXz4cMeq7kOGDMHUqVMxa9YsvPzyywCAW2+9FRdddFHUr+AO8DvoRCdcNCILMfu3OPYbrDb85+SJmBrGnAghhEQX9RYb5v/fLnQ9+3q0fjg0LcGE0wd0CWdaBMAJaQL3TRmExDgTTC4LyD7wxe4wZkVU4nBSF9z02hb8eqweBXeOR+vqBQ9fNATxxiHY/N3XYc1PFQoLC3HOOec49u+55x4AwPXXX4+8vDx8+qn9j5GjRo1y033zzTeYNGkSAODZZ59FbGwsrrjiCtTX12Py5Ml4/fXXYTQaHfFvv/027rzzTsdq79OnT/f67vVohBN0vdI6AIxGIDfXue+tTEuMjMZXXv7q6aRGCIEHVv2CZf/zIO5Yuxd/vXi4tvPI5KewD2HVyOjone8Yeien04MPevXOVav1PDK6Dmo2/HoUH2w9COP4GZhZZUH/NP8an/WqrJHRKdaHUk3AlWcOdH5iwWjEzulXY8WOw856Jk+md9HQhzyvow+NEAKHaxrRIzUeMBqRceY41FhssNiasbWiDqe3aE7qmQyr1cvT8mj0ToJJkyZBCM+lLp20d6yVhIQEPP/883j++ed9xnTr1g1vvfWWphwjHU7Q9UpSkn2bnAysWuV+zLNMS4yMxhsy9QRAM6BXOkzGQzgjJ0v7eWR0wfDB18rTgdZoyU1WI6NTvA/RuzBrZHT+NKqNi0jyLpj5yWgcse38LvN3HhldBzXnnNITd00ehPEDu6F/3wwpjc8YlTUyOtX7UHIyst9fioc2luKx//vJXvbJJ0BcLP6+aieS42MxY1RWG43ti/yWFbiP21fg/iK//RW4o9Q7lfuQbfkKrD9Q7bxGA7vB6KEpqwOmPb8OAsBX95wNQ3IyDKtW4Z+lx9G3WxK6Jcfp0juiBlzFXa+0ruDY2Ajk5dm3rXiWaYmR0XhDpp5OagwGA+48sx++iS3C6X1SHZqG+Qs6dh6Z/BT2IawaGR298x1D7+R0evBBr945tO38LvN3HhmdH43Z0oT/Xb0bjTbn4bt/1x+nv7VIXe/YhxwxaU8+jpmjMp1ljy9E1fFaLP5vCZ7O/xn7K+vdJPlbSnHmA8tx9asbcNd7Rbj61Q0484HlyN9SKp+bTH4R4J3Kfei8vJXu1+jJr/D5Q/9EZWWNI6Zbgn1l9rLj9fjtqNlR78ieifbJuU69I4oQ3jXqSKjR4yruXnUeMUfKDouzbn1VLFldLJqbm6U0UvkFwQeu4q5mH6J3kecDV3GPzD6k0iruf1i8QfSfu1Jc/o9PI8K7gGkC4F0ofWhP47mKe/2RY+L9jfvEPe8XicbGRodu7kdb7XH3feaI7z93pRhw36diwNyV4ottZVHpnVR+CvQh11XcPa9Ra9nFz/3HTfPfnytEVb1cm6LZu86s4k6CA5+gEwLgwx8PYl/XLLy1uRz1Vpt/ASGEEF1gM8Rg/d7j+KToANb/chS2Zuf3K/90zknISk/A+J7NYcyQBJIEkxFXjO2L/71ipOMd6tamZnxQ2PKU3OO96sJg/6f0gs+K3foGCS1u3hu8fOXAYMC28lpU1zu/Sz5+YDekJfAtCkQ9+B10QgDcNqEPEh64H2d88AqS4jgsCCGEAPk7j2DBH5eg/O1tjrKMZBMea3kLyPgTumP1nDPx1Zf54UuSBJ2Nvx1De3NvAfvHpQtKjmFsvzTfgSRobN533G+MALCjrJrXiCgPn6DrldZVTE0m4OabnfveyrTEyGh85eWvniBoDHFxuGF0LwzK7uII+ebnw9hRafCpkTpXhPkQMo2Mjt75jqF3cjo9+KBX71y1Ws/jR5e/vRy3L/sJ5akZbuVH6qz446UPIH9PJQAgPtbjn1Kqe8c+5Dvmuuu9ao6a5d53faimAc3NAhbXD+LpwTsF+tCRWrnvVR+qaZA7l468I+rBR4V6JSHBvk1MBBYvdj/mWaYlRkbjDZl6QqDZd9SMez7chrrGGIzffQSTc7K0tSkYPvhaeTrQGi25yWpkdBHeh4KmkdHpwTsZnT+NauMikrwLZn4yGkdsO7/L/J2nHZ2tWWDBZ8UQgM+Pyy5YtQfnj+rXqfO0G6OyRkYXKT643gde+Bfg5VN0PVPj26/LEZeArfur8GChEYXNO/DUZaOi27vOaGR0EprGpmYcrgcGpMhfI6lz6cA7oi58gq5XGlr+glhfD9xyi33bimeZlhgZjTdk6gmBpld6PKaPzMTAVGDCwG6OGNstt2D9T2XO7yLWmds/V4T7EDSNjI7e+Y6hd3I6PfigV+8c2nZ+l3WiTYV7K1Fe5eNJWwutH2nuzHna1amskdFFjA8u13n2HV41Y/t3RVZ6Any9TM0AICvd/jqvb3cfgaXZgAZrs9t5CnaWo6F1jZuo8S68fWhHWRWm/r/v8erPRgzv3f7H1g1CICstHuNa/00XjDZFkHdEbThB1ytWq3O7ZIlz31uZlhgZja+8/NUTAk18rBELLs7B7UNsiGv5+OIX28owIeFsXL10i/PVHc99j/z/Fvs+V4T7EDSNjI7e+Y6hd3I6PfigV+9ctVrP047uUE0nPi6runfsQ75j3ljqVWOMMWD+xTkAAINwXxCwdX/+xTkwxhhw57kn4p7hTbj1rAGO8xx+92NctXQzTntsDY6bLdHnXZj6UN9uSahrbEJ9E9z+oNbmGrVs5593gu931uvMO6I2nKAT0g5xRvvW/l3EnTic3NXteEWNBbdf+gDydx4JQ3aEEEKCQUc+0kz0wdRhWXhxxhBk1hx1K8+sOYoXZwzB1GFZAACDwYD+KcDJvVIdMfu6ZqJXShxO6JGMLklxjvKPtx3E1zsPwtLEtwDIUHrMjDcKyxz7aQkmLL52DB4abcPAjGRHec9a90+2ZKbF48UVCzH1FPf1JAhRFX4HnRA/2JoF8j4rtu94vl4FgAECC9b8ivPHDgx9coQQQgKGEPalusf274rMtARUVHv/mLtBNCMzPRHjBnZDs83HWgYk6ph6SgbOf+lmFGwtwSGbET2NNowbORDGJyvb1Z16YCe+/9M4HI1x/kGnyRCDJ74qwRGzFa9dNybYqUc8R2obcf6za9FgbcaIrJMxqqV8RJ907P/RPXbN4tuxvXCn/RqlJmBc91gYH1wf6pQJ0Qwn6HolPt65nT/fue+tTEuMjMZXXv7qCbGmcG8lKtr5LqIwxKC8utH761WiyIeAamR09M53DL2T0+nBB71656rVeh6XMhEXh6Xfl+CHX49iSqr9I81503Nw+1ubAQgIl28fGwDAYMD8aYNhjDGg2SZ/HiW8Yx/yHTPvAb8a4yMPY+LJvexxjY3AIw9LnScmIQE9XPIzP5yHi4ZnYv1vxzHhhG5Yvdt+6IONpdhUcgRXPfw0RkeKdyHoQxnx8bhweDbKKuuQdMuN7Z7LeP/9zmsE2K+Tqj6oNv6IGgiiK0pLSwUAUVpaGu5UhMViEStWrBAWiyWoms6e6+PCvaL/3JV+f1Zs2R+SNtU1Wh3nPF5rDppGa37RqFE9P5U1KuendVzQu9BqPHWu162u0RqQc/12pFYMeuBz0X/uSvG31z5xaL7YViYmLFzjdq+fsHCN+GJbWafaxD6kjqa9/hSO/Ga88L3oP3eleO27Xx3Hm2zNwtpkC0tuoTxXq6axsVF8/dNB8fsXvheVdY2O4/WWJtHc3OxVc7zWLHVfCGV7QnmuzmhKSkqUmRsQO/wOul4xm+3bujpgyhT7thXPMi0xMhpvyNQTYk2nvosYRT4EVCOjo3e+Y+idnE4PPujVO4e2nd9lHWhT/wTgoYuG4JELT8GwrsJxeOrANHz3n7/j3WtH4p9XjcK7sybguz+Nx9S/3BC53rEPecSYnWWXXBJ27+7NHYw/nJqNaU/8xXH8v7sPY9zja/D3G/IU8y44PjQL4Kn8nSjcW4mX7njCcTzBZITBbPZ/Ls/rqLIPqo0/ogT8iLtesdmc2y+/dO57K9MSI6PxlZe/ekKsaX29SkVVA0SbowCEcLxepc13EYPhgylEGi25yWpkdFHUhwKqkdHpwTsZnT+NauMikrwLd5tctRrOY7Y04R+rduGmURno01J23cQBsFqt+Pzz7W4a45erMLFvGpDW8hWm6urI9o59yHfMV1+F3buJJ3bHxB4m4IrljuNf/XQIx8xWVJcddNPsrQVszcJ5K4vgPnSkthGpJvtXSYwxBjx0YQ6+3b4ft199JfDPu9uvxxPP66iyD6qNP6IEfIJOiB/afb1Ky0/rqzt2H6rF1qO+3pRKCCFEBR5cvh2vfV+Cv3y2y/sfXglRiPkX5+DNq4fhus3/5yjbd8yMZ7bFYtL/fut8v3qEsviH/fjd099g5bYKR9mZgzLwwOQTkN7Ip71Ef3CCTogEPl+v4vLqjnqLDXe9vxWv7TLi3Y2lYcqUEEKIP+acNwgn9kjGnWf0Bf+kSlQn1hiDswZ2xaCjzn9b/HqkDklGgRMykpFgMjrKPx56LgpLq9DcHDl/empsaobZYsPqnw6FOxVClIAfcdcrCQnO7auvOve9lWmJkdH4ystfPWHSTB3VB+ePbkLB707FoXqb/dUdvVNg7HkTkJAAY4wBvxuUgYOVtTh/SM+o9SEgGhkdvfMdQ+/kdHrwQa/euWolNAeO12P73mpMaYnpnxaH1XefjZgma+B9UN079iHfMYv+FTHeTTq5B/421obTzhrmCGkwmvDIxXNQ9+aPWDY7BWMyk5X0+4dfj6JHajxOSLeX3fy7EzGwT3ecN7g7vvjiQId88IrndVS536k2/ogahHuVOhJauIp78FfEfOcjd80vh2oCeh6u4h56jer5qaxROT+u4h4ZGk9dR1dx/7msUgybny9OfvBzsauiOuD5qaxRPT8VNKqt4t4ZzaHqBnH3e1tE7jNrhc3mXO38jfW/ib99tkPs2H8s7H3opf/sEf3nrhQ3/rsgoOfhKu5cxT2a4Efc9UrrCo61tcDQofZtK55lWmJkNN6QqUcVjY+yJJfPpWwsPoDz//41HvpwC2ytHzdTuU1h9q7TmnC2id6FViOj04MPevXOoW3nd1kLA7onYXS/rhjSKxnxF10QfB9U9459yCPG5TvOY8dGtHc9DFY88+g1yL9lNGJiDA7NW9+XYPF3Jdh2oMoRa2sWEEKE3O/zB6QiPjYGWekJsFZVB6cPeV5HJfudmn2IqEFsuBMgYaK52bktLnbueyvTEiOj8ZWXv3pU0Ujotuyvgi3GiLrGJsQY5DRhbZNC3umiD9E77RoZnR580Kt3rlovmu0HqnBid/vHOA0GA56/ajSSGutguvO74PugunfsQ75jdu6MCu8MQjj2RXEx7vldP3z+SxXOO6Unviu3H/p8WzmeXrUT14/Jwi1B8rupGfj3ur2IiYnBLSMzgOJinNA1AevuPxfdU+Ltb0QIhg+e11HlfqdaHyJKwAk6IUHk1gl9MPTWmRhV+A0MBvsMvVkIrs5ICCFB4oX/7ME/Vv2MO889CQNbytKTTEAT77xEfxgATBmcgSmnnQCr1eooX7WjAqXH6nG0zuIoE0Jg16E6nNyi6yw/HTdg8Q8/I9FkxPQT09CyOo99ck4I8Qkn6IQEmTP2bgXinCusPrr6VzROuQPzrTZwmQ5CCOkYNpfVqQv2VeGsbl1gdDmemZaAZmFfGG6Ar3fdE6Jznr5sBKYNy0JOmvMPVz+V1+CCxZtxyo3P4/+ahdu48sRmiEHB3uM4ZKtBT6MN4wwxMAKot9iQ2PJvnmFdBXJzeuLcU3qhexIHIyGycIKuVxIT7dukJCA/375txbNMS4yMxhsy9aiikdF5HN9zqBZLN5VBjJqGi45YcEZ3Dfn5+mRSoDW+CJN3Ic1PZY2MTg/eyej8aVQbF5HkXZjatGrHQfzt852O/Rs+2IHMVb/gr+edhN+3aP5ndCr6d0/CiOxUfP753tD7oKh3AdXI6CLGh0Rn2YoVuvEuKS4WF47IApqaHDG7fjmI+NgY9M85AcaUZEfsJ0VlOGJ2avNLarDg4U9R/vY2R1nPhz7FgLe34XhDEz6/8ywAgMEA/OvqUTCZTG7nCboPntdRyX6naB8iSsAJul6JjXVup0xpe8y1TEuMjMZXXv7qUUUjo/M4flLPFLxx0zj8uL8KZwzupS0/S1NoNFpyk9XI6PTQh+iddo2Mzp9GtXERSd4FMz8fmq1HDfj3+q3wfLtzRVUD/vLxdsRdPQoXx8bCAODU/t3cPs6ruU1R4l3ANTK6SPHB9T5w3nnOfx8FKzcZXZi8u3R0b5yX0wvHzRaHD1X1VsxbsQNWWyzOObsOJcfqcfu7RW3G4WELcGjvcQDAhl+PYfyA9M63SasPntdRxX7XGY2MTqt3RAn4hSyFyMvLg8FgcPvJzMx0HBdCIC8vD9nZ2UhMTMSkSZOwY8cObSerqbFvq6uBtDT7thXPMi0xMhpvyNSjikZG5+X4Wb3iccclYxxlNQ1WfLY3BvUWW/jbpLh3SreJ3oVWI6PTgw868c7WLLDst5g2kwJX8pashe14le+AUPmgmHdB0cjoIsaHGmdZZpbuvUtpNKNP/0zHfpXZirNOykCfZIH+3ZOw4LNir+OwtSwjJQ4TT/Ty8cBQ+uB5HZXsd4r2IaIEMeFOgLgzdOhQlJeXO362bXN+fOjpp5/GM888g0WLFmHjxo3IzMzE+eefj5qamnZqlMCb3rNMS4yMRiYflTUyOj+ahz/5CWvKYnDn+1sDn5/KGhmdHvoQvdOukdHpwQcdeFe4txLHLe0vW3U0KR0Fpe1M0H3lEgwfFPIuaBoZXaT5UEvvPPf7dU/Cy38Yjb8Mt6FwbyXKqxrarepIrQUFJcfkziOTnxaNt+uocr9TrQ+RsMMJumLExsYiMzPT8dOjRw8A9qfnzz33HB588EHMmDEDw4YNw9KlS2E2m/HOO++EOWvSGa48rTe6xgncMemEcKdCCCFKcqimUS6u1hLkTAjRJzGGDozDmvYn8YSQ9uF30BVj9+7dyM7ORnx8PMaPH4+FCxfihBNOQElJCSoqKpCbm+uIjY+Px9lnn41169bhtttu81pfY2MjGhudN9TWp+1NTU327+c1NdkXjGtqAlq/r+dZpiVGQtP6/UC37wn6qUeLxjXe2oE2+tXItElCM7ZvGh4abcPQzGSHrvhAFQakdkGSl/xc2261Nkm1SYsmEryL+D5E78Lqg9ZxQe9C54OwWGAwGNAtsb31pJ10TzS2OUfIfVDEO/YhOY21qclRZE1o2ad3XtskPQ6TYsPgg+/rqIJ3EdOHJPj222/x97//HZs2bUJ5eTmWL1+OSy+91HF82bJlePnll7Fp0yYcPXoUW7ZswahRoxzHf/vtNwwcOLBtxQA++OADXH755QCAAQMGYO/evW7H586diyeffLJD+UYiBiFEe1/pIiHkiy++gNlsxsknn4yDBw/isccew86dO7Fjxw78/PPPOOOMM3DgwAFkZ2c7NLfeeiv27t2LVatWea0zLy8PCxYsaFO+ePFiZGRkBK0tRDtVFuDprUYkm4A/DrGhm8frQhttwH0F9r+tPT2uCfESvy+1aAiJdjgu1EUI4PuDBnxbEYM/DrGhSxywYLMRxy2A9zc0C3SJA+aPsSEmEC9wJrqB9wF5moW645DXUTtHjhzBLbfcgtLSUvTp08dv/BdffIHvv/8eY8aMwe9///s2E/Q333wTJSUlyM7OxqxZs9pM0G02Gw4fPuxW5yuvvIKnn34aFRUVSElJAWCfoN98882YNWuWIy4lJcVxPJrhE3SFmDZtmuP/hw8fjokTJ+LEE0/E0qVLMWHCBACAweB+xxNCtClzZd68ebjnnnsc+wcOHEBOTg4mn3suevfpY/9XUG0tkJJifx+GvVL3Mi0xEhqr1YrVq1fj/PPPt7+CQ6JeLRoAbXWB0Mi0SYNm24EqJO8qQrdEIy6/cALi42LdNGarDfcVfA0AOPfcc5GenODXBy2aSPQu4voQvQurD1rHBb0LjQ8ffPQzDtYfQ1nSSbjy3IHYdmwN/r3L/q9u1ycLhpb/PnbByZgypn/4fVDAO/YheY05LtFxH5hy+ulI6pZO73y0aUru+TANOIY/v7fV9zicMRJThvYKuQ/nnnsuUPCt1+uogncq96Hf/e536AjTpk1zm7N4cu211wKwPyn3htFodFsEGwCWL1+OK6+8ss3kOzU1tU2sHuB30BUmOTkZw4cPx+7dux2ds6Kiwi3m0KFD6NXL9+u64uPjkZaW5vhJTU0FAMQ2NMBkMsHU0ABT9+72rcnkvUxLjIym5QbnOC5ZjxZNG10gNDL5adCMGZCBz28ahVcevRopNqtDY+uZ6dC0YjLFSrdJiybSvIu4PkTvwu6D1nFB7wLrQ+lJw/HEZztgQ4xDc9fpfbBg+lDcnTsYJpMJI7sLPH/VSPRMc/9YUWZ6Al6cMQQXTTxZDR84/pT0oT2N4z7Qry+989Omi0b1wYszhiCz2v0JaGb1Yfs4HNUnTD44nzm2uY6KeKdyHwLsX4Otrq52/Lh+RTaYbNq0CUVFRbj55pvbHHvqqafQvXt3jBo1Co8//jgsFn2sM8In6ArT2NiIn376CWeddRYGDhyIzMxMrF69GqNHjwYAWCwWrF27Fk899VSYMyWBpntyHLpXHXTsL9t2EItufB7/OlSH/v2SwpgZIYQElmYhcMPlC7BvYxlO7NMN1wzpCgAY3y8d49PSADi/IzllaC+cfUovDM/7EgDw+hVDcdao/jDKrL5NCAkIU0/JwPkv3YyCrSU4ZDOip9GGcSMHwvhkZbhTI50gJyfHbX/+/PnIy8sL+nmXLFmCIUOG4PTTT3crv+uuuzBmzBh07doVBQUFmDdvHkpKSrB48eKg5xRuOEFXiHvvvRcXX3wx+vXrh0OHDuGxxx5DdXU1rr/+ehgMBsyZMwcLFy7EoEGDMGjQICxcuBBJSUmYOXNmuFMnQaTJ1ox/rSvFr937YPWuo7ilX49wp0QIIZppFsB/dx/BOUMyYTAYEGMw4MZNn+L72+dhaHa6X73R5cut4/qlu+0TQkKDUTRjYv8uzvdqi+Zwp0Q6SXFxMXr37u3Yj4+Pbyc6MNTX1+Odd97Bww8/3ObY3Xff7fj/ESNGoGvXrrjsssscT9WjGU7QFWL//v24+uqrceTIEfTo0QMTJkzAhg0b0L9/fwDAfffdh/r6esyePRuVlZUYP348vvzyS8fH1kl0EmuMwYfXjsTrl9+JO+5/AaH5wBEhhAQeW7PA01uNKN+wGe/dOgETTrD/I+uGTZ/hxsvfcv5jnxBCSEhJTU1FWsunlkLFRx99BLPZjOuuu85vbOt6XHv27OEEnYSO9957r93jBoMBeXl5gfm4SesiDKmpQFWVfduKZ5mWGBmNN2TqUUUjowuQD916dcM9//eifd9qc4T9VF6DCScl+m+TiybgPijuXdRpZHR68E5G50+j2riIJO86kJ/58DEktewbYww4IU2gHnE4WN3giDF0tE2O87XzuywQbeL4096mSPEhPtFZVlZO76KhD3leR5V9UM27ELNkyRJMnz4dPXr4/3Toli1bAABZWVnBTivscJE4vdLc7NyWljr3vZVpiZHR+MrLXz2qaGR0QfZh1ltbUN1g7ZCm3mKD2dJk/2mwwPzrXvvW237LT6MNgdX4KGtPI4RQuz/oqN8poZHR6cGHEHsn9u3zPWY9xm1VvQV//XArxj63Hr8crHbEnJfdjC/uPB3n5/TSeE+xuecZBh903+9kdJHmAwDs30/voqEPeV5HlX1QzTsJamtrUVRUhKKiIgBASUkJioqKsG/fPgDAsWPHUFRUhOLiYgDAzz//jKKiojYLXe/ZswfffvstbrnlljbnWL9+PZ599lkUFRWhpKQEH3zwAW677TZMnz4d/fr161T+kQCfoOsVs9m+rasDhg2z/0Wt9WMtnmVaYmQ03pCpRxWNTJuC4UOCc5G4uyefiLQEU4c0E55a6+WE+/zsxzpeQxNYjWeZb83Y/l3x4cyhMKjaH6K936mmCYQPCT4WXIwkH0LonaitxWVPfoFNffa6BHobs4DnWJ/83HdumgVbAnQfqjMDifFqjSWOv8jy4fAxZ9m404Ajh+hdpPchz+uosg+qeSdBYWEhzjnnHMd+6+ucr7/+erz++uv49NNPceONNzqOX3XVVQDaLjr32muvoXfv3sjNzW1zjvj4eLz//vtYsGABGhsb0b9/f8yaNQv33Xef5rwjCU7QCYlgZozOdvx/6fEGVGaehBFe4hJNRpzarws27TsestwCTeHeStRbm8E17AkJD7WNNmzqk+M/MESM3b8DiaYzw50GIYToikmTJtk/1eiDG264ATfccIPfehYuXIiFCxd6PTZmzBhs2LBBa4oRDyfohEQwBoMBAGBpasaflv+E4j/8Hf/86TAuGJ/WJu7dW07DipVfYMqUXMc7L1FdA2Rn2b+vlZbadh/21xutWvWlUxcIjZdz+9KY9+7H2H/+EBpDCSFeyd9ejvkrtruV9UqNR24vM+69+nwgxogpz/0XFVUNWLD6RVy+6k2v94c24xzQfE9J7HERDC/8MdRWEEIIIUGFE3TifbEIzzItMTIamXxU1sjoQuCDxdaMzNR4/GZtxMjsVK8ag8GAeCOQFBcLk6ll6McZgYQ4+zYutu0+AKtBuOsCofFybp8akzGo3kWkRkbH8add4y0m2jQyupbj+dvLcftbm+H5vORgTSPerInB+N1HcdGoPrhr8iCUH6rChf8uQpKP+0ObcQ5ov6eo3If00O9kdJHmQwq9C6lGRqdF4+06quyDSt4RJeAEXa+0DlBvr7TxLNMSI6Pxhkw9qmhkdMHwwdLUJjwlPhYv3TgepcdGoHf3JIfmeMURdEmKg61Z4IeSY9h0xIDuJccw8aSe9ncHR4J3ru1NS1W3P6joXUc0gcovknzwMpYClp/KGhldy3Fbs8CCzza2mZy78vgXOzFtRG9cPa6fveDg/s7lp6APQdd4i1FZI6OLFB9c7wMV5c4/IgcrNxldpHjXGY2MTqsPntdRZR9U844oAVdx1ytNTc7tqlXOfW9lWmJkNL7y8lePKhoZXQh9MNhs6Ff4X0fM9n3HcMbjq3Hv+1twxlNf4w+vFeKN3Ub84bVCnPnU18jfXk7vIlEjo9ODdzI6PfgQZO/WbC9DeVWD77phQHlVIwpKjoW3TSr1IT30OxldpPkAAGvW0Lto6EOe11FlH1TzjigBJ+h6pb7evjWbgalTnau6eyvTEiOj8YZMPapoZHRh9OHTTftQZwM+2lKGCo9/YFdUNeD2tzYjf/O+CPCu3qWsXt3+oKR3HH9R70MAvTtYD7y5YR++233EcfzosVrf9bpwqKYhvG1SqQ/pod/J6CLGB5ffMZdeSu+ioQ95XkeVfVDNO6IEnKATEqXcN2kA0utrvB5r/bjqgjW/wmbgbYAQvVFe3YjPB58Bq63ZUbbpSAwe/b+dWLbF+RH1gd0TperrmZoQ8BwJIYQQPcJ/mRMSpWzcX42qRN+LgQjY/5Fe0Gdo6JIihIScBqsN+9N6OPaFEJi6eDNmXzoPOw/VOcpPShM4e1AGxvTr6igb1zcdWekJMPisXSArPR7jBnYLTvKEEEKIzuAEXa/ExDi3OTnOfW9lWmJkNL7y8lePKhoZXRh9OFQn9x2jQ4OH07tI0sjo9OCdjE4PPnjsCyFga3Yu6bam+CCG/e96zLnyEUeMwWDA2L5pGFp1ALVWZ+zJ6QKLrxuDP0zo76jXGGvE/Ivt7z73nKS37j847RT7opMK+SClkdGx32lvU6T5AACnnELvoqEPeV5HlX1QzTuiBFzFXa8kJ9u3KSnAjh3uxzzLtMTIaLwhU48qGhldMHzwtfK0h6Znj/T2z9HCkfl/w6HmWPQMRG6yGhld63HX9qYkq9sfVPSuI5pA5RdJPkiOpWC2ybZtOwpKjuHQnir0TE3AuG3bnZPdDp7nbyuLsWzzfiy4eIjj8Ak9ktHULHDwpBw0JyU7/ir/6o0TEHPzRKnzTB2Wghf/MAbzP92Bg9WNjpDM9HhM62XGlKG9Ou1DxPahQGm8xaiskdFFig+u94HCwvZXcad3gdPI6LT64HkdVfZBNe+IEvBPKHrFarVvLRZg8WL7thXPMi0xMhpvyNSjikZGF0YfxvVOQZbR5vOjqQYAmWnxeOHz7Tjr6W+waW+lot5ZXcqs6vYHJb3j+FPZh/yiUpz58Ge4+tUNuOu9Ilz96gac+fBnyC8qbfc8R156DXM/2IKrXlkP0djoOI+lqRmVZiuKSqsc4QMzkvHdPWfi266/IqbJOZZimvyMJY/8pw7Lwpo/ne44/PqNp+Gbe36Hkd1FuzqV/A5ZH1K83yntXVja5PI75vWl9C4a+pDndVTZB9W8I0rACbpeaWhwbmfNcu57K9MSI6PxlZe/elTRyOjC6IPR0oj5Hz0JwPdHU/80sQ/6l+5CRrIJw3unO+oQ9fXwiQ68U1ojo9ODdzI6hX3I316O29/7EeVN7r+GK5oMuP29H+2vQQSw7UAVVu6Lwf9tq3DUm/zn2fi4qBwbfj2GskNVjvNcf3p/rLjjDNxz/iBHfQaDAX0SDDDc2nnvjBbn0/NxA7t5f9LPPqR0vwuYRkYXaT4AwJ/uoHfR0Ic8r6PKPqjmHVECfsSdkChm6q71eHHGECz4qsTtXcaZ6QmYf3EOpvZLxjXn/hWHDxxGXGzLd1gBXP/+Dgzp0xW3TzoRyaZ2Pm5LCOkwtmaBBZ8V29+mYHAfX8IQAwOABZ8V4/ycTGz8rRKrD8RA/FiOS8f0BQAkNjXiwckD0SerG7ommhzak3raF4W0Wq0ghBBCSGTCCTohUc7UUzJw/tiBWL/nEL787w/IPWs8Jp7U0/70q7oaBgA9U+Ic8Zt6D8G3v1Ziw74q3HTmQCSbjOFLnpAopKDkmNsfzDwRAMqrGlBQcgzjB3bD+B7NmDYs0y3mxtN6A2lpQHV1kLMlhBBCSCjhBF2vGI3ObW6uc99bmZYYGY2vvPzVo4pGRqeID8YYA8YP7IajPwmMd/1oqhfNqUP74rWrhuO3Wht6pSU4nsat+ekQJpzYA1115p1yGhmdHryT0Snig+fK6mt3HfJdjwuHahpwwdCemHlSMy4YmRW43GR0vjT+YB9Spt8FVSOjizQfAGDyZHoXDX3I8zqq7INq3hEl4ARdryQl2bfJycCqVe7HPMu0xMhovCFTjyoaGV0wfPC18nSAfDCsWoVzPcKONQIL39+K+Fgjvrz7d8gOpXeu7U1OUrc/RHu/U00jo/OnCfJYwqpVeG7NLrxbsA93nXsSWt6dgZF9u7RfVws9UxOCk5uMzqsmqf3zBCq/SOpDgdJ4i1FZI6OLFB9c7wOffNL+Ku70LnAaGZ1WHzyvo8o+qOYdUQIuEqdXWldwbGwE8vLs21Y8y7TEyGi8IVOPKhoZXZT4UGcFTuyRguG905GdGOOIaW4WIfDOZbXRRkvEeRdwjYwuSvpdp9sUQh/MNWb886FXMOv1AvvT8hZNY4MVB6sbsWlfpSM2NycTvVLj233DQlZ6AsYN7BaQ3ALnncTKv+xDHH+d0YSlTS79+vGF9C4a+pDndVTZB9W8I2ogiK4oLS0VAERpcbG9oKpKCMC+bcWzTEuMhMZisYgVK1YIi8UiXa8WjVddIDQy+QXBh7pGq+g/d6XoP3elOF5rDpl3DQ2N4lhtoyOm/milOP+Z/4hnV/4ozLHxQfOu7vAxR3vrDh+Lrj4UQf1OOe8C4IPWsXTweK1YsOQTsXr7AYfEWnlc5Mz5QPSfu1IUl1U5NL/8Wi7W/3JEVNXWu+X2xbYyMWDuSjHgvk8dOfRv2R8wd6X4YluZct65jcVGK/sQx1/E+NCexq1fmzr4u0wH3kWKD8drzT6vI71rX1NSUmKfG5SWCqIGfIJOCJEiJsaArsnOxeRWFh/GroO1eL+oAjHCFsbMCAkeQgjsOWJGncn5cfNVOw7htV1GvPrdb46y2BgDZm/4EH+bciJ6pMY7yk/onoQJJ3RHYpz7d/6mDsvCizOGILPmqFt5Zs1RvDhjCKYOywpOgwghhBCiNPwOOiFEEzOG90RCWjIM9fWIf8j5Hb6PNu3H5MHdw5gZIdoRQrh99PyKl9dj42+VeKX/SOS2lI3t3wVZSQLDstPctHds+BA4dTGQEg9U+/8I4dRTMnD+SzejYGsJDtmM6Gm0YdzIgTA+WelXSwghhJDohBN0vWIyObc33+zc91amJUZG4ysvf/WoopHRRbEPMXFxuGhEOlBf79Cs/+Uo7v1wK3qmxuOvQzrpQxR7x36nng/7K+tx61tFOFpnwZrbxzliTuqZgh/3V6FiysUOzUk9U3D/SBsumDq4020y3nQjJp7UA0hMtI+lm25U2zt/6LgPdUoTqDZFunfhbtN119O7aOhDntdRZR9U846oQbg/Y09Ci+M76Ap8z8Tr93mCoAnluUKh8fm92SDk1lHdf3cdFuf84xsx7+MiN02TrVnzeVzbW9do1ZxbZzShPFe0aVTMb/0vR8RDy7eJDzbuc/StA0erxcD77f9fdtw5ro7VNopGqy0s7QnluWQ0nmNRrz5Ekkb1/FTQqPA7RmWN6vl5/Q66x3UMV26hPFdnNPwOunrwO+h6paHBvq2vB265xb5txbNMS4yMxhsy9aiikdHpwQeX/TMHZWD13Wfjr7knO8Irqhpw1pNf4eU/PwVbnVneB8fxBpeyhojwIagaGZ0e+p2ETpjNKL7tHrz57W40WG0OzeZnl+DNDXux+qeDjtjk+Fj8a+YYrLnnbGSahKPerslxiLM2qutDSPtQg/dYFdqk0lji+NOuCUubXPr17DvoXTT0Ic/rqLIPqnlHlIATdL1itTq3S5Y4972VaYmR0fjKy189qmhkdHrwwWPfGGNASrzz2zNv/7AXZdWN+OoYENNE79jvAqTxUtZgteFIg7vmOtMYPPz5Lmw7UOUo+90HL+Om07IxY3Rvt1NMG56Fk3qmwNDUFDk+hLoP+UMvPnD8RZ8PAPDGUnoXDX3I8zqq7INq3hEl4HfQCSFB5c7Jg9A30YATrv4rDIbbAQCWpmZ8sLkcl8XGIcGPnhBfCJcF3dbuOoxblm5EZoIR17WUGQwGTCopxMHpl7vphh36FcPOPxHmhKSQ5ksIIYQQ4g8+QSeEBBWTMQZXjMzE2AM/Oco+KCzFQ/l7cPnMpyCECGN2JBJ58T+/4Nz//Q9W7DjsKDu5VwqsNoEaq/0PQK384/N/4s2rh+O0Ad3CkSohhBBCSIfgBF2vxMc7t/PnO/e9lWmJkdH4ystfPapoZHR68EGDpkuSCb3TEzCjbxwMCc5n6Lbmthqbyfnu9YIKM2yPqNkm9rvAaxptwL/X7cXd7xeh2RTniDlW14hfD9eh4ECtoywrPRH/+ctZyBtjQ1xsTFT5EHCNjM6Xxh968UEH46/TbYo0HwBg3gP0Lhr6kOd1VNkH1bwjahDuVepIaOEq7uquohkNq7h3RNNotbmtjr1+90Ex8uHPxJvrfnWUfbGtTIx7fLWjvf3nrhQTFq4RX2wrC2pugdJRI6+rabCKtT8fEuv2HHFoPlq2Qgx+6HPRf+5KsftgtSN2Z3m1WFNcISrrGjuVXyjHUjT0O67iHnka1fNTQcNV3NU5F1dxD4+Gq7irB5+g6xVzy2radXXAlCn2bSueZVpiZDTekKlHFY2MTg8+aPQurrEecRdOc5S99UMpjlsM+HG/fTGv/MLfcPubm3CwutGtqorj9bj9rc3I316uVpvY7zqkqbhoBhqOVzv2l900D9e9VoAX/rPHERYbA9wwsT/mTj0Fac1WR72DM1MxeUgvdBHWiPchsvqQ2XusCm1SaSzpod/J6CLGB5d+fckl9C4a+pDndVTZB9W8k+Dbb7/FxRdfjOzsbBgMBqxYscLt+LJlyzBlyhRkZGTAYDCgqKioTR2TJk2CwWBw+7nqqqvcYiorK3HttdciPT0d6enpuPbaa3H8+PFO5R4pcIKuV2w25/bLL5373sq0xMhofOXlrx5VNDI6PfgQIO+enDEMlw204fazT4CtWWDBqt3w9u10YbAvC7bgs2LYmr1ERJIPOu1317xZhAnDbsb6X485NGNXf4y+XRLQv7v7wm1/OX8Qbp90InomxUadDxHZh/yhFx/03u9kdJHmAwB89RW9i4Y+5HkdVfZBNe8kqKurw8iRI7Fo0SKfx8844ww8+eST7dYza9YslJeXO35efvllt+MzZ85EUVER8vPzkZ+fj6KiIlx77bWdyj1S4CruhBAliI+NwVmZAn26JqKg5BjKayyAweA1VgAor2pA4d7K0CZJOsS+o2bkfbYDR2sbcVNfZ3l2Wjximm0oOVaPc1rKcg6X4L+zTwPS0sKSKyGEEEL8M23aNEybNs3n8dZJ9G+//dZuPUlJScjMzPR67KeffkJ+fj42bNiA8ePHAwBeffVVTJw4ET///DMGDx6sLfkIgU/QCSHKcaimwX8QgEM1jf6DSEjYfKAaT36xE6t+PuIoS0804ZufD2Hr/ipUW5yx957dH1v/eRVuGtc7DJkSQgghJNy8/fbbyMjIwNChQ3HvvfeipqbGcWz9+vVIT093TM4BYMKECUhPT8e6devCkW5I4RN0vdK6cnZCAvDqq859b2VaYmQ0vvLyV48qGhmdHnwIgnc9U+Xejt4zNR5HW/5/dfFBZHdJwJBuCYiJFB8isN8JAZRWmlG0vwYXjchGXEvMd6W1eGntL5g+PBNTWjTpcSY8/fsRODEjEb8Vfe+oo1ePdOBf/y+ifYhojYzOl8YfevFB7/1ORhdpPgDAon/Ru2joQ57XUWUfFPKupqYG1dXVjv34+HjEB2nF92uuuQYDBw5EZmYmtm/fjnnz5mHr1q1YvXo1AKCiogI9e/Zso+vZsycqKiqCkpNShHuVOhJauIq7uqtoqrjytFZdZzVNtmYxYeEaMcBl9XbPn5ELVon6hkaxYsUK0dDQKEYuWCX6z10pCn875qiz0WoTzc3Nnc4tEG2KVI21ySYOVtU7NMuXrxCjWrzevNfp9ea9x8Tcj7Y6VtgPVX6d0XAV945puIp75GlUz08FDVdxV+dcXMU9PJrWVdw9f+bPn++3DgBi+fLlXo+11rtlyxa/9RQWFgoAYtOmTUIIIR5//HFx8sknt4k76aSTxBNPPOG3vkiHH3HXK60rONbWAkOH2reteJZpiZHReEOmHlU0Mjo9+BAE74wxBsw//wRACHh+C93QUvbkjOEwxtiPVjVYMbpvF/RKi8fIrrGOel9a+wsmLlyDNy68RU0fFO93//1xH0bOXYFblxY4QgwGYPzAbhjdrwsam5odmtHdTHjy9yMwdUBq1PkQdRoZnVeNxMq/uvCB/U5KFzE+uPTrsWPpXTT0Ic/rqLIPCnlXXFyMqqoqx8+8efN85xRgxowZA5PJhN27dwMAMjMzcfDgwTZxhw8fRq9evUKWV7jgBF2vNDc7t8XFzn1vZVpiZDS+8vJXjyoaGZ0efAiSd1NP7o4XVyxEz5Q4t/LMmiN4ccYQTB2W5SjrmhSHf984Duvvn4xYCEe9BSXHUFFjQUxZmeM8NQ1WvP9LDP5vWwWEEOH1QaF+t+S7Ekxfsgmf27o6YgZ0SUBdbDxKKxtgtTl1/+/KEVg++wxMOKF71PkQsPxU1sjofGn8oRcf9N7vZHSR5gMA7NxJ76KhD3leR5V9UMi71NRUpKWlOX6C9fF2b+zYsQNWqxVZWfZ/202cOBFVVVUoKHA+IPjhhx9QVVWF008/PWR5hYvYcCdACCG+mLprPc649VQMf2Y9AOD1K4birLEnwvik99XbY2Lcn7cvvn4sNhXvx6BF6x1lBSWVWHcoBuVf7cGlY5xLi//UYwB6NzRF/SLi9VYbPinYh237j+M0lz/Rlh4z48fyWmzoOxwXtJT1SY9H/pI7MGj3VhiNMbA221/NYvCxuj4hhBBCopva2lrs2bPHsV9SUoKioiJ069YN/fr1w7Fjx7Bv3z6UlZUBAH7++WcA9qfimZmZ+OWXX/D222/jggsuQEZGBoqLi/GXv/wFo0ePxhlnnAEAGDJkCKZOnYpZs2Y5Xr9266234qKLLor6FdwBPkEnhCiO0WXSPa5fOoxC4ileCwkmI84Y2BU96447yvp0TcSkrGb8fkxvt9g//s8DGPXsevzw61FEC41Nzdi0txJb9jn/oGEwGPDIJzvwdkEpjjQ4Yy87tQ/+eclgzN7woVvsKUf2ul0DQgghhOiXwsJCjB49GqNHjwYA3HPPPRg9ejQeeeQRAMCnn36K0aNH48ILLwQAXHXVVRg9ejReeuklAEBcXBy++uorTJkyBYMHD8add96J3NxcrFmzBkaj0XGet99+G8OHD0dubi5yc3MxYsQIvPnmmyFubXjgE3S9kpho3yYlAfn59m0rnmVaYmQ03pCpRxWNjC4YPvian0atd4kuZYmdzm9wZir+Z0AzLvjdQIekOsaEmOxsGBoNyMlOA2INQH4+3is+huVbd+Dqcf1w4bCeHTqPltykNO3oquutSDHEIL7l+Nvbj+LRz3fi3FN64rU/jAby85GQloKrx/VFUlwMTDW7HdphvdMxrFcy8NHbUdiHfGiiYSyF1LtE77EqtEmlezh//2nXhKVNLv16xQp6Fw19yPM6quyDat5JMGnSJOdXBL1www034IYbbvB5vG/fvli7dq3f83Tr1g1vvfWWlhQjHk7Q9UpsrHM7ZUrbY65lWmJkNL7y8lePKhoZXTB8sDR1XKPlPMHUyOhaj7u2N0j5paUk4pv5F+JIbSNSE0z2wilTsPatTfih5BjOGpThiLXamvH6+l8x8cTuGJqb6/y4d5i9e/mnGMzZ8A3euGkczhrUA5gyBWP3H0e35Dh0S45z0yy4ZBisVis+/3x3+/VGSx/yVRYNYynU3vlDLz6E+r6vmkZGFyk+uN4Hzjuv/X5O7wKnkdFp9cHzOqrsg2reESXgR9z1Sk2NfVtdDaSl2beteJZpiZHReEOmHlU0Mjo9+BB072pcymqCml9Gc6Pb/v1n9cHj/zPMbUG6H/dX4fHPf8J1izdApHdx1Hv84FEIifPY0tOxfts+fFJ0AOu37YMtPb1D7Sk9Zsaf3yjAtdc84aZLirW/o/znihqHZniqAZseOg//uHyk2v2B4y+0GhmdV02N91gV2qRSH9JDv5PRRYwPLv06M4veRUMf8ryOKvugmndECfgEnTgn6+2VaYmR0cjko7JGRqcHH6LUu/5dE9G/v/11HlarFYB9IbrJp/RE93gDYmqcv+Suf38Hyq9dhEX7qjBumPeV5vJ3HsGCa/6J8re3Ocqyrvkn5u88gqnj2mp2lFXhm62lGJYxCJNaypLijPis+DDQdwQqzVZ0bZFd0LcZz998DrK6pth/+dbU2J/uuy7opnJ/iNI+pKxGRidTr4wuGn1gv5PTRZoPtfQupBoZnRaNt+uosg8qeUeUgBN0QkjEYLbaAFM8YLEBliZYrU1otAFmSxNMomUianGP8dzXogHg0A3ulYLnZ44GqmtgbolpqGvErsN1qE/tjoxkE8wtmq+LK/D2nhiYfjoIa7MBc5b9BJGa4damitTuuH3ZT3g6xoS0RBN+d2JXx7H87RV4fu1ezMiZ5Jigd0+JR975J+Dkm65C8lznd7i6JwAZKaF7JQoJHEII1Pvpd47+2oG+6lMD+B8XXjRmqy0s/hBCCCF6ghN0QkjEMPafPwD3fAz8Y51LaSzuK/jaPdAzJiAaLzovMee+vMlDE4OCd7Y6dz1eUSYMMTAAuO+jHyEArLh9guPYmSdl4Nfy4/jdZ5vdNDec1hvY9yNgjAGJbASAy978EZv2t3waQ0u/09hX/Y4Lr/USQgghJJhwgq5XWldwTE4Gtm+3b1vxLNMSI6Pxhkw9qmhkdMHwweZj5cwo9S6xSyrG9u+Kwr3e330eDbRe0T5dE1DdYHWUjz+hO8b37wKMXRT+fqeaRkbnT6PAWKrf8iM2vbfPd4yCjO3fBYkmI5qavCyyp7c+FChNoNoU6d6FpU0uK1oXbKR30dCHPK+jyj6o5h1RAk7Q9UpMjHPbt69z31uZlhgZja+8/NWjikZGFwwfbD4+Zhql3hmMRnz4x4mot9rsq6DV1AKpKYDBAKvVilWrvsSUKbkwmVpWX/eICYQGQFtdBzTNvUfg/uXFvv1p4a9TTsHEE7rj852B8Y7jz49GhbHUpw8A+wS98MHJSGqsD1i/86kB/I+LdjSJ3dKdby8Ip3cq9KFAaQLVpkj3Ltxt6tOH3kVDH/K8jir7oJp3RAl4hfRKba19W1MDpKe7LxrhWaYlRkbjDZl6VNHI6PTgQwi8MxgMSIqLRVJjPZJ6dLNv42KRFBeLeCMc/+81JkCaNroOaPp0lXvnaM/UhIB7J63xFqOyRkYXCT5kO98QEOh+51MjMy7a0Rhaf3+E2ztV+1Ak9DtVvQtLm1z6c3YWvYuGPuR5HVX2QTXviBJwgk4IIUFmbP+uyEpPgI9njjAAyEpPwLiB3UKZFiGEEEIIUQxO0AkhJMgYYwyYf3EOAMAgmt2Ote7PvzgHxhhfU3hCCCGEEKIHOEEnhJAQMHVYFl6cMQQ9a4+5lWfWHMWLM4Zg6rAsH0pCCCGEEKIXuEicXklJsW9TU4GqKvu2Fc8yLTEyGm/I1KOKRkYXDB98vYuY3oW3TRKaqacNxBkDumD4M+sBAK/fMBZnZSbAmJ4mfx6Zc0Whd0HxQYWxVFbufJVZakrkeBfM/CKpDwVKE6g2Rbp34WhTfKKzrKyc3kVDH/K8jir7oJp3RAn4BF2vNDc7t6Wlzn1vZVpiZDS+8vJXjyoaGZ0efKB3HdIYyw44dsf17wLjgf30Ts99aP/+0Ocmo4sE71T1gd5p14S7Tfs7eD+md9o1MjqtPnheR5V9UM07ogScoOsVs9m+rasDhg2zb1vxLNMSI6Pxhkw9qmhkdHrwgd51TDPuNJd9M73TqpHRRYIPne0PevZOVR/onXZNWNpkdpaNO43eRUMf8ryOKvugmndECThBV5QnnngCBoMBc+bMcZQJIZCXl4fs7GwkJiZi0qRJ2LFjR/iSJIQQQgghhBASMDhBV5CNGzfilVdewYgRI9zKn376aTzzzDNYtGgRNm7ciMzMTJx//vmo4fsMCSGEEEIIISTi4QRdMWpra3HNNdfg1VdfRdeuXR3lQgg899xzePDBBzFjxgwMGzYMS5cuhdlsxjvvvNO5k3pbLMKzTEuMjEYmH5U1Mjo9+EDv5DUp9C5gGhmd6j4Eoj/o1TuVfaB32jXeYkKl8RyPwTqPjC7SvFPJB2/XUWUfVPKOKAFXcVeMO+64AxdeeCHOO+88PPbYY47ykpISVFRUIDc311EWHx+Ps88+G+vWrcNtt93WsRO1DtC0NKC62v2YZ5mWGBmNN2TqUUUjowuGD5amjmu0nCeYGhldtPahinLgkVUt+6n0TqtGRudPo8JY6mx/4PjTrpHR0TvfMdHig+t9oKIciGvnn8b0LnAaGZ1WHzyvo8o+qOYdUQI+QVeI9957D5s2bcITTzzR5lhFRQUAoFevXm7lvXr1chzzRmNjI6qrqx0/rR+Hb2pogNVqhbW+Htb8fPvWavVepiVGRmO1AoDzuGQ9WjRtdIHQyOQXJB9asVqb6F2k9aHVq53Xr76B3oW5D4VyLHnVdLY/cPyp5wO9U9IH35oG5xhcvZreRWwfcv6hpc11pHd+NUQtDEIIEe4kCFBaWoqxY8fiyy+/xMiRIwEAkyZNwqhRo/Dcc89h3bp1OOOMM1BWVoasrCyHbtasWSgtLUV+fr7XevPy8rBgwYI25YsXL0ZGRkZwGkOCSqMNuK/A/pfhp8c1Id4Y5oRIh+D1UwcVroUKORCiZzgGowNeR+0cOXIEt9xyC0pLS9GnT59wp0MAQBAlWL58uQAgjEaj4weAMBgMwmg0ij179ggAYvPmzW666dOni+uuu85nvQ0NDaKqqsrxU1xcLACIkh9/FBaLRViOHhWWxET71mLxXqYlRkJTV1cnVqxYIerq6qTr1aLxqguERia/IPhwvNYs+s9dKfrPXSkOV1bTuwjrQ8dTuziu3/HyQ/QujH0olGPJl6bT/YHjTz0f6J1yPrSnOV5+yDkGU7vQuwjtQ4crq31eR3rXvmbXrl0CgCgtLQ32dIdIwu+gK8LkyZOxbds2t7Ibb7wRp5xyCubOnYsTTjgBmZmZWL16NUaPHg0AsFgsWLt2LZ566imf9cbHxyM+Pt6xX93y3ZPY2FiYTCYgNhaor7dvTSa0HHQv0xIjo2nBZDLZc5E9t0aNmy4QGpk2BcEHk5smlt5pbFO4fDA11DvLY2Nhondh60PhGEuemk73B44/9Xygd8r64E1jio11Hm9o2ad3EdiH2rmO9M6vhqhFrP8QEgpSU1MxbNgwt7Lk5GR0797dUT5nzhwsXLgQgwYNwqBBg7Bw4UIkJSVh5syZHT9hTIxzm5Pj3PdWpiVGRuMrL3/1qKKR0enBB3rXMc0pp3SuPTK6aPUuGn3obH/Qs3eq+kDvtGvC3aZTTqF30dCHPK+jyj6o5h1RAk7QI4j77rsP9fX1mD17NiorKzF+/Hh8+eWXSNXyyoTkZPs2JQXYscP9mGeZlhgZjTdk6lFFI6MLhg++Vp6md4HLL5iawkLnqt0pyfROq0ZG50+jwljqbH/g+NOukdHRO98x0eKD632gsLD9VdzpXeA0MjqtPnheR5V9UM07ogT8E4rC/Oc//8Fzzz3n2DcYDMjLy0N5eTkaGhqwdu3aNk/dpWldsdFiARYvtm9b8SzTEiOj8YZMPapoZHR68IHedUzz+lLHrrm2AeZXlsBcWw+zpcnx02iDc7+2vm2Ml7JOa7zFBEjjNz8tmgD54LgWFlvQffCqee0Nl/5h5fgLpUZGR++0tylifHBZwfr1pfQuGvqQ53VU2QfVvCNKwFXcdcb+/fvRt29flBYXo8+QIfb3IaanA1VV9vcjAm3LtMRIaKxWKz7//HNccMEFzu+/+KlHiwZAW10gNDJtCoIP5oQk5LQ8cdv68LlIT06kdxHUh8wZPZFzz8eaxi+JborvPR1JPbpx/EX6fYjeKedDexrz4WPI+cc6+xh85vdIOnKI3kVgH5p0Xi5G/u1rr9eR3rWvGTlyJAYOHMhV3BWCT9AJISSEJFobMbZPWrjTIIoxtn9XJJr4K5kQQgjRO/wOOiGEhBADgA+vHYH6xGSgugbIzgLKyoE0+1oSVqsVq1Z9iSlTclv+Ct42xrMsIBovMYHQSLUpTD6YExIx9rGvAADr556N9OSEoPngT5PYvQsMNTUB72+EEEIIiSz453q9YjQ6t7m5zn1vZVpiZDS+8vJXjyoaGZ0efKB3HdYYYmORFBeLpMQ4JJ1ztn0bF+v4iTfCue8txktZpzXeYgKk8ZtfGH1oJSnOGHQf2tMYDAaOv2i5D9E77Zpwt2nyZHoXDX3I8zqq7INq3knw7bff4uKLL0Z2djYMBgNWrFjhdnzZsmWYMmUKMjIyYDAYUFRU5Hb82LFj+POf/4zBgwcjKSkJ/fr1w5133omqqiq3uAEDBsBgMLj93H///Z3KPVLgE3S9kpRk3yYnA6tWuR/zLNMSI6Pxhkw9qmhkdMHwwdfK0/QucPmprJHR6cE7GZ0/TTSMJfYh7RoZHb3zHRMtPrjeBz75pP1V3Old4DQyOq0+eF5HlX1QzTsJ6urqMHLkSNx44434/e9/7/X4GWecgcsvvxyzZs1qc7ysrAxlZWX4xz/+gZycHOzduxd//OMfUVZWho8++sgt9tFHH3WrIyUlpdP5RwJ8gq5XWldwbGwE8vLs21Y8y7TEyGi8IVOPKhoZnR58oHeh1cjo9OCdjE4PPtA77RoZHb3T3qaI8cFlRevHF9K7aOhDntdRZR9U806CadOm4bHHHsOMGTO8Hr/22mvxyCOP4LzzzvN6fNiwYfj4449x8cUX48QTT8S5556Lxx9/HJ999hmamtz/cJ6amorMzEzHj14m6BBEV5SWlgoAorS42F5QVSUEYN+24lmmJUZCY7FYxIoVK4TFYpGuV4vGqy4QGpn8guBDXaNV9J+7UvSfu1IcrzXTu0juQ/QurD6EcixFm3f0gd5Fkg/taeoOH3PcB+pM8fQuQvvQ8Vqzz+tI79rXlJSUCACiuLhYVFVVOX4aGhqEPwCI5cuXez3WWu+WLVv81vPqq6+KjIwMt7L+/fuLzMxM0a1bNzFy5Ejx2GOPicbGRr91RQP8iDshhBBCCCGE6JicnBy3/fnz5yMvLy/o5z169Cj+9re/4bbbbnMrv+uuuzBmzBh07doVBQUFmDdvHkpKSrB48eKg5xRuOEEnhBBCCCGEEB1TXFyM3r17O/bj4+ODfs7q6mpceOGFyMnJwfz5892O3X333Y7/HzFiBLp27YrLLrsMTz31FLp37x703MIJJ+h6pfU1PyYTcPPNzn1vZVpiZDS+8vJXjyoaGZ0efKB3odXI6PTgnYxODz7QO+0aGR29096mSPMBAK67nt5FQx/yvI4q+6CQd6mpqUhLS/OdR4CpqanB1KlTkZKSguXLl8PUngcAJkyYAADYs2dP1E/Q+R10neH4DnppabhT8f59niBoQnmuUGh8fm82CLlp1UWbRvX8VNaonF8ox1K0eRdKjer5qaxRPT8VNK73gbpGq3L5hVujen5ev4PucR3DlVsoz9UZTet3xbXMDaDxO+hVVVViwoQJ4uyzzxZ1dXVS5/rss88EALF3794O5xlpcBV3vdLQYN/W1wO33GLftuJZpiVGRuMNmXpU0cjo9OADvQutRkanB+9kdHrwgd5p18jo6J32NkWMDw3Ostl30Lto6EOe11FlH1TzToLa2loUFRU53m9eUlKCoqIi7Nu3D4D9PedFRUUoLi4GAPz8888oKipCRUUFAPuT89zcXNTV1WHJkiWorq5GRUUFKioqYLPZAADr16/Hs88+i6KiIpSUlOCDDz7AbbfdhunTp6Nfv36dyj8iCPdfCEho4Sru6q6iKdsmruIeRX2I3oXVB67izj4UFB/onXI+tKfhKu7R0Ye4invnV3GXfYL+zTffCABtfq6//nohhBD//ve/vR6fP39+u3oAoqSkRAghxKZNm8T48eNFenq6SEhIEIMHDxbz58+Xftoe6fA76IQQQgghhBBC/DJp0iQIIXwev+GGG3DDDTdo1gPAmDFjsGHDBq0pRjycoOuM5uZmAEB5RQWQmgrU1NgPHDgAVFfb/9+zTEuMhKapqQlHjhzBgQMHEBsbK1WvFg2AtrpAaGTaFAQf6hMS0VR9pGX3AGqSEuhdpPYhehdWH0I5lqLNO/pA7yLJh/Y09WUHnPeB5mYk0ruOt0kRH3xdR3rXvqa8vByAc45Awo9B+PsTBokqNm7ciHHjxoU7DUIIIYQQQogiFBQU4LTTTgt3GgScoOuOpqYmnHTSSfj2228RE2NfI3DSpEn4z3/+4xbnWaYlxp+mpqYGOTk5KC4uRmpqqlQ9WjS+dIHQyOSnig/0Tk0f6J0+fKB3+vKB3qnlA73Tlw/0rmOa7du3w2w2Y/To0c5PB5CwwqugM2JjY5GUlOS2AmJcXBz69OnjFudZpiXGn6a65SM3vXv3dnvvYnv1aNH40gVCI5OfKj7QOzV9oHf68IHe6csHeqeWD/ROXz7Qu45p+vbtG9L3nxP/xIQ7ARJ67rjjjnb3AxUjo9GanyoaGZ0efKB3odXI6PTgnYxODz7QO+0aGR298x1DH+hdZzQyOnrnOyZYPhAFCOcS8kTfVFVVCQCiyvUVEEHQhPJc0aZRPT/6oL5G9fxU1qieH31QX6N6fiprVM+PPqivUT0/rW0iwef/t3f3QVGcdxzAn703DgEBQeFO3i4VA46kWKTk0OoZpWiDgKlGkpoTGzRGnGBj2lRsRaOhJKZ5sw5GR60xLTGJSmosJk2IAUdNBIrQiBFFFAQUX0blHeHbP5jbYdk9Xi7mbof8PjM34+3u955nl/O3++zd7dIn6MRhnJycWEZGBnNycvpBM/Zsa7hl5N4/2g7yz8i9f3LOyL1/tB3kn5F7/+SckXv/aDvIPyP3/tm6TuSHRxeJI4QQQgghhBBCZIA+QSeEEEIIIYQQQmSABuiEEEIIIYQQQogM0ACdEEIIIYQQQgiRARqgE0IIIYQQQgghMkADdELuM7ruIiGEEEIIIcQWKkd3gPx41NbWsuzsbHb8+HHW0NDAOI5jPj4+LDo6mi1fvpz5+/s7uov3hZOTEzt9+jQLDQ11dFfspr6+nmVnZ7Njx46x+vp6plQqmcFgYImJiSw5OZkplUpHd5HIXHNzM/vnP/8pqg9TpkxhTzzxBHNxcRnS6129epW98847bN26daJ5tbW1zMPDg7m6ugqmd3Z2shMnTrBp06YJpt+4cYOVlZWxn/70p2zUqFHs+vXrbOfOnay9vZ0tWLBg0P/XH3jgAfbpp5+y4ODgQS3f2dnJDh8+zCorK5lOp2Pz5s0TbYfa2lqm1WqZt7c3Y4yxwsJCtm3bNnb58mUWGBjIUlNTmdFoFGT++te/svnz57PAwMBB9cPi0KFDrKioiM2ePZsZjUaWn5/PXnvtNdbd3c0ee+wxtmzZMlGmtbWV5eTkSNaGmTNnDql98uMk59rAmGPqw3CoDYxRfSDEKgffh538SBQWFsLV1RWhoaFIS0tDZmYmXn75ZaSlpWHChAlwc3PDsWPHhvy6ly9fxpIlS0TTW1paUFhYiG+//VY0r7W1FXv27BFNP3PmDHbt2oWKigoAQEVFBZYvX44lS5bgiy++EC3/u9/9TvKhUChgNpv55/25efMm3njjDaxYsQIbN27E5cuXRcuUlJSgqqqKf753715ER0fDz88PU6ZMQU5OjuRrr1y5EgUFBf22L+Xtt9+G2WzGvn37AADvvvsuQkND8eCDD2LNmjXo7OwULH/q1Cm4u7sjPDwcRqMRCoUCTz31FBYuXAgPDw8YjUbcuXNHsq2mpiZs374dycnJmD17NubMmYPk5GTs2LEDTU1NQ+57Q0MDNmzYIDmvpqYGd+/eFU3v6OjAV199JZp+/fp15Ofn48aNGwCAxsZGZGVlYcOGDThz5syg+2QwGHDu3LlBLdvR0YGDBw/i1Vdfxd69e61ug5qaGjQ2NvLPCwoK8OSTT2Lq1Kn4zW9+g+PHj4syr732Gqqrqwfdb4t//etfWLduHf+aX3zxBebMmYPY2Fi88847kpmWlhbs3LkTS5YswezZs/Hoo49i5cqV+PzzzyWX//bbb6HX6+Hh4YGEhAQsW7YMS5cuRUJCAjw8PDB27FjJ/8v9KS0thUKhEEyrq6tDZGQkFAoFlEolzGaz4D3R0NAgynz99ddwd3cHx3Hw9PREUVERDAYDgoODMW7cODg7O6O4uFiQeeuttyQfSqUSa9as4Z/3ZTQacevWLQDAtWvXEBYWBo1Gg+DgYGi1WgQEBKC2tlaU+fe//w0AyM3NhUKhQHx8PF588UXMmzcParUahw4dEmQ4joNSqcSsWbPw/vvvo729fcDtmZ2dDZVKhYiICIwcORLvvfce3NzckJKSgmeeeQbOzs548803BZnKykoEBgbCy8sLOp0OHMfh0UcfRVRUFJRKJRYsWCCqJxZUG8R9odogr9oA2K8+DLfaANheH+xZG4DhUx9sqQ3EcWiATuxi8uTJWLVqldX5q1atwuTJk4f8ulI72u+++w6BgYHgOA4KhQLTp09HXV0dP19qR5uXlweNRoNRo0ZBq9UiLy8Po0ePxqxZszBz5kyoVCrRIJ3jOISHh8NkMgkeHMchMjISJpMJM2bMEGR0Oh2uX78OAKiqqoKvry98fX0RExMDPz8/uLu78ycILCZNmoT8/HwAwI4dO+Ds7IznnnsO2dnZWLVqFVxdXbFz507RtrGsf3BwMLKyslBfXz/g9nzppZfg5uaGX//61/D19UVWVha8vLywadMmZGZmYvTo0Vi3bp0gM2XKFKxfv55/vnfvXkRFRQHoOQERHh6O5557TtSWnA+85HzQZcnJ9cDLloMuk8mEpKQkyT61t7fjiSeegMlkEkw/ffp0v499+/aJ/q5msxkPP/wwTp06hf/85z+YPHkyIiIicPPmTQA97wWO4wSZWbNmISUlBXfu3MHmzZvh5+eHlJQUfv7TTz+NxMRE0bb28/NDUFCQ4MFxHMaOHYugoCAYDAbRunIch6tXrwIAli5divDwcP7/7fXr1xEdHY3f/va3goybmxsuXrwIAIiKikJWVpZg/pYtWzBp0iRRO7t370ZCQgLUajW8vLyQlpaG8vJyUZ8sQkNDsX37dgBAfn4+tFottm7dys/fvXs3QkNDBZk5c+bgmWeeQVdXFwDgL3/5C+bMmQMAOHfuHIKCgpCRkSFqi2oD1QYLOdcGwH71YbjVBsC2+mCv2gAMv/pgS20gjkMDdGIXWq0WZ8+etTq/oqICWq1WNP3jjz/u9/HGG2+ICmRiYiLi4uLQ2NiIyspKzJ07FwaDAZcuXQIgXVSNRiPWrl0LAMjJyYGnpyfS09P5+enp6YiJiRFkMjMzYTAYRAN3lUpldQfReyeblJQEk8mE5uZmAEBbWxvi4uIwf/58QWbEiBF83ydNmiT6ZOIf//gHJkyYINnW559/jrS0NHh7e0OtViM+Ph6HDh3id4h9PfDAA9i/fz+Anp2WUqnEe++9x88/cOAAxo0bJ8g4OzvjwoUL/POuri6o1Wo0NDQAAD777DPo9XpRW3I+8JLzQRcg7wMvWw66nJ2d+z2oKi8vh7Ozs2h9FAoFOI4TPSzT+74X9Ho9vv76a/55W1sbEhISEB4ejhs3bkjWBk9PT/5Tj46ODigUCsFrlJSUYOzYsYLMsmXLEB4eLvq0pL/aYFkny/th/Pjx+OSTTwTzv/zySwQFBQmmubu74/Tp0wCAMWPG8P+2OH/+PEaMGGG1natXr+KVV15BSEgIFAoFIiMjsX37dtG3Xpydnfk6BABqtVrw3rl48aKonREjRgg+AWpvb4dareZPUubm5orWB6DaYMlQbZB3bQDsVx+GW20AbKsP9qoNwPCrD7bUBuI4NEAndmEwGLBr1y6r83ft2mX1EyVrO9reO9zexowZg7KyMsG0FStWICAgABcuXJDc0Y4cORKVlZUAegaYKpVKcJazvLwcPj4+ov598803GD9+PFavXo2Ojg4Ag9/JSg3uT548CT8/P8E0Ly8vFBUV8etWWloqmH/+/HnRAUrftjo6OrBv3z7ExsZCqVRCr9cjPT2dX2cLqR3t//73P/55dXW1aEcbGBgo+HlCXV0dOI5DS0sLgJ6ds9TJFzkfeMn5oAuQ94GXLQdder0eubm5ovW0OHjwoOgkj7e3N3bu3Inq6mrJx+HDh0V/VxcXF9FXBjs7O5GYmIiHHnoIZWVlkhnLQQ0AuLq6Ck5IXbp0SfL9ffDgQfj7+2PLli38tMEM0K9duwag5+/ad9nq6mo4OTkJpsXHx+OPf/wjACA2Nlb0ScuOHTsQHBwsasfyXuitoKAAixcvhouLC1xcXATz/Pz8+J/MXLlyBRzH4fDhw/z8o0ePimqXXq8X1NFbt26B4zj+fVZVVSVaH4Bqg2V9qDbIuzZYcvaoD8OtNgC21Qd71QZL/4ZTfbClNhDHoQE6sYutW7dCo9EgNTUVubm5OHHiBE6ePInc3FykpqbCyckJ2dnZopxer8fBgwetvu5///tfUYF0c3OT/J3PypUr+R1JfwN0QLyTra6ultzJAsDdu3dhNpsRFhaGsrIyqNXqQe1k9Xq9YPAL9BzU9N0hLVq0CE8//TQAYMGCBfjTn/4kmJ+ZmYmwsDDJtqR2tJcuXUJGRgYCAwNF28FgMCAvLw9AzycaCoUCH3zwAT//8OHDoqKflpaGiRMnIi8vD/n5+ZgxY4bgDPaRI0fwk5/8RNQPOR94yfmgC5D3gZctB10ZGRlwd3fH5s2bUVpaivr6ejQ0NKC0tBSbN2+Gp6en6DeCsbGx2Lhxo2h9LEpLS0WfboSFheGjjz4SLWt5PwQEBIjeCyEhIYITaZ988gl/8gmQPqlmUVtbi0ceeQSzZ89GfX39oAbov/rVrzBv3jx4enryX0e0OHHihOhE4ZkzZ+Dl5QWz2YyNGzfC1dUVixYtwssvvwyz2QwnJyfs3r1bkFEoFJLvBYvbt2/zn45apKamIjg4GJs2bcLPf/5zLF68GCEhIcjLy8ORI0cQFhYm+sRm8eLFmD59OioqKlBVVYWFCxcKPqE5evQo/P39Re1TbaDaYCHn2gDYrz4Mt9oA2FYf7FUbgOFXH2ypDcRxaIBO7Ob9999HVFQUVCoVf/ZSpVIhKiqKvyBZX3PnzsWf//xnq68ptaONjIzEu+++K7l8amoqPDw8REX1oYce4gemQM9Z2N6/hSssLJT8hL+3nJwc+Pj4QKFQ9FtUw8LCMGnSJLi6uuLAgQOC+V999ZXo7OqVK1cQFBSEadOm4fnnn4ezszOmTp2KpUuXYtq0adBoNIIDo95t9bej7e7uxmeffSaYtnbtWowePRopKSkwGAxYs2YNAgICkJ2djW3btsHf31904bu7d+/i8ccf5/+u0dHRgovaffrpp4JBvoWcD7zkfNAFyPvAy9ZBWVZWFv+7VIVCwX+yodPp8Morr4iWP3DgAPbu3Wt1fW7evIm///3vgml/+MMf8Mtf/lJy+c7OTsTHx4veC+vXr7d6IUag5+cvjz32mNX53d3dyMzMhK+vL5RKZb8D9OTkZMGj7/+bF154AbGxsaLc+fPnkZSUBDc3N762qtVqREdHS57gHKg2SGlqakJKSgomTpyI5cuXo6OjA5s3b4ZGowHHcTCZTKLXvHr1Kh5++GH+bxoUFISSkhJ+/ocffoi3335b1BbVBqoNvcm1NgD2qw/DrTYAttUHe9UGYPjVB1tqA3EcGqATu+vo6EBdXR3q6ur4r4VbU1BQIBg499XU1ISjR48KpmVmZvK/a5Py7LPPiopxdna26CtCvaWnp/OfYvenpqYGubm5Vq8kun79esHjyJEjgvkvvPACkpKSRLlbt27hxRdfxIQJE6DVaqHRaBAYGIgnn3wSp06dkmwrKCiI/+rgYN27dw+bNm1CXFwc//uknJwc+Pv7w8vLC8nJyVbXrbW1VfJKp/2Ry4FX3/eD3A+6APkeeNk6KLOoqqrC8ePHcfz4ccGJnvuhs7MTt2/ftjr/3r17Q76adXNzM9ra2gZcrqioCG+++Sb/+0VbNDU1obW11er87u5uNDQ0DKq23i+tra1W79Jgce7cOdFJz4HIpTY46oTN960NCxcuHNa1ofenkoPV3d1tdZ612mDJDLU2WHJDqQ+vv/76kOuDpZ2h1IbBXATQWjtD0dzcPGBtAMT1YaC27FEbgOFZH4Z63EAchwMAR9/qjRDy43bx4kXW0NDAGGPM19eXGQyG+/ba9+7dYy0tLWzkyJGS87u6ulhtbe2Q7vva0tLClEolc3Jy6ne54uJiduzYMWY2m5mnp+eQ+s1Yz/1/lUol02q1VpcBwK5du8a6u7uZt7c3U6vVQ25nqNra2lhnZydzc3OzukxlZSVrb29nISEhTKVS/eB9IsMT1QZpP/baoNFo2OnTpwd9j3F7ZuTePzlnhpL7IWsDY46tDyUlJaywsPAHqw+OqA1kaOioiRDicAaDQbRzrampYRkZGWzXrl2Dfh2pjEqlsrqDZYyxuro6tmHDhiG1c+PGjUH1LSIigkVERFjt20Bu3rw5YIbjOObj4yOYdr+2nTVarZZptdp+M8HBwUNqp7W1lRUXF7NRo0axCRMmCOa1tbWxDz74gJnN5mGdkXv/7LkdKioq2MmTJ1l0dDQzGo3s7Nmz7NVXX2Xt7e1s0aJF7JFHHrGaMRqNLCQkhJ09e5a99dZbVjMqlYpduXKF7d+/f9AZW9qRyri4uLCzZ8+y1atXD5iJjo5mDz744KDasZZ76aWXfrB1Gkr/emdUKtWAmeeff15yHbu6ulhWVhbz8vJijDH2+uuv2z0j9/7JOfN9chYGg4F5eHiwPXv2sMrKSqbX65nZbGb+/v6Sy1vcunWLz+h0OrZ48WLJTN9jh7655OTkAQfng22rb6agoIBVVlayrVu3DjozlHY4jmMajWbI247YkUM/vyeEECus3ZuUMvJp635lvvvuOwQGBvJfWZw+fTrq6ur4+VJXyx1uGbn3z57bIS8vDxqNBqNGjYJWq0VeXh5Gjx6NWbNmYebMmVCpVKI7YFBG/v2zJcNxHMLDw2EymQQPjuMQGRkJk8mEGTNmOCQj9/7JOWNrTqfT8T/dq6qqgk6ng6+vL2JiYuDn5wd3d3dUVFT0m/H19R0wY2tuuGWI49AAnRDiELbc454y8u+fLZnExETExcWhsbERlZWVmDt3LgwGA38bJ6mB3HDLyL1/9twORqMRa9euBdBzDQxPT0+kp6fz89PT0xETE0OZPhm598+WTGZmpuQtSfu7gJa9MnLvn5wztuZ6Xy8hKSkJJpMJzc3NAHpugxYXF4f58+d/74w925JzhjgODdAJIQ7R371Je9+jlDLiAYyc+2dLZsyYMSgrKxNMW7FiBQICAnDhwgXJgdxwy8i9f/bcDr1ve9nV1QWVSiW4PVd5ebnoCsWUkX//bF2nb775BuPHj8fq1av5ix8ONPizV0bu/ZNzxpZc70Gm1OBe6irptmTs2ZacM8RxFI7+ij0h5MdJp9Ox/fv3s+7ubslHSUkJZSQycu+fLZnW1lbRxaK2bt3K4uPj2fTp09m5c+eGfUbu/bPnduhNoVAwrVbLPDw8+Glubm7s9u3blOknI/f+DSUTGRnJiouLWWNjI4uIiGDl5eWM4zirr23PjNz7J+eMrTnL/Pb2dtH1V3x8fFhjY+N9ydizLTlniGPQAJ0Q4hARERFWB6CM9exI0OcmE5SRf/9syYSEhLCioiLRslu2bGEJCQksPj5eNG+4ZeTeP3tuh6CgIHb+/Hn++YkTJ1hAQAD/vKamhul0Osr0yci9f7auE2OMubq6sj179rD09HQWExPDurq6JJdzREbu/ZNzxpbczJkz2c9+9jN2584d0Um+y5cvM29v7/uSsWdbcs4Qx6CruBNCHOL3v/89a25utjp/3Lhx7Msvv6RMn4zc+2dLZt68eSwnJ4c99dRTouX/9re/se7ubrZt27ZhnZF7/+y5HZ599lnBQfrEiRMF8/Py8kRX+6aM/Ptn6zr1lpSUxKZOncqKi4sHfXsre2Xk3j85Zwaby8jIEDwfMWKE4PmhQ4fYL37xi++dsWdbcs4Qx6H7oBNCCCGEEEIIITJAX3EnhBBCCCGEEEJkgAbohBBCCCGEEEKIDNAAnRBCCCGEEEIIkQEaoBNCCCGEEEIIITJAA3RCCCGEEEIIIUQGaIBOCCGEEEIIIYTIAA3QCSGEEEIIIYQQGaABOiGEEEIIIYQQIgM0QCeEEEIIIYQQQmSABuiEEEIIIYQQQogM0ACdEEIIIYQQQgiRARqgE0IIIYQQQgghMkADdEIIIYQQQgghRAZogE4IIYQQQgghhMgADdAJIYQQQgghhBAZ+D8hNTsP8vo/WAAAAABJRU5ErkJggg==' width=1000.0/>\n",
|
|
" </div>\n",
|
|
" "
|
|
],
|
|
"text/plain": [
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"class CokeOvenServiceProgram:\n",
|
|
" \"\"\" as implemented in excel sheet provided \"\"\"\n",
|
|
" def __init__ (self, duration, start, load, T0, q0):\n",
|
|
" self.start = start\n",
|
|
" self.end = start + duration\n",
|
|
" self.duration = duration\n",
|
|
" self.load = load\n",
|
|
" self.T0 = T0\n",
|
|
" self.q0 = q0\n",
|
|
" \n",
|
|
" self.a = 0.6 - (self.duration - 4) * 0.01 # 최소 열량 / 최대 열량 비율\n",
|
|
" self.b = 6 + self.duration / 2 # 감급 시작에서 감급 완료까지 시간, 정수 -6 에서 감급 시작 정수 중간 시각에 감급 완료\n",
|
|
"\n",
|
|
" t5 = self.lowest_heat_duration()\n",
|
|
" q5 = self.q0 * self.a\n",
|
|
"\n",
|
|
" t1 = self.b / 4\n",
|
|
" t2 = self.b / 4\n",
|
|
" t3 = self.b / 4\n",
|
|
" t4 = self.b / 3.5\n",
|
|
"\n",
|
|
" t40 = 13 / 4\n",
|
|
" t30 = t40 * 0.8\n",
|
|
" t20 = t30 * 0.8\n",
|
|
" t10 = t20 * 0.8\n",
|
|
" t00 = self.b / 5.9\n",
|
|
"\n",
|
|
" tt1 = 3\n",
|
|
" tt2 = 3\n",
|
|
" tt3 = 5\n",
|
|
" tt20 = 3\n",
|
|
" tt10 = 3\n",
|
|
"\n",
|
|
" q1 = q0 - 1 * (q0 - q5) / 3.7 \n",
|
|
" q2 = q0 - 2 * (q0 - q5) / 3.8\n",
|
|
" q3 = q0 - 3 * (q0 - q5) / 3.9\n",
|
|
" q4 = q0 - 3.7 * (q0 - q5) / 4\n",
|
|
"\n",
|
|
" q40 = q4\n",
|
|
" q30 = q3\n",
|
|
" q20 = q2\n",
|
|
" q10 = q1\n",
|
|
" q00 = q0\n",
|
|
" \n",
|
|
" qq1 = q00 * 0.9\n",
|
|
" qq2 = q00 * 0.83\n",
|
|
" qq3 = q00 * 0.77\n",
|
|
" qq20 = qq2\n",
|
|
" qq10 = qq1\n",
|
|
" \n",
|
|
" T1 = T0 - (q0 - q1) * t1 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" T2 = T0 - (q0 - q2) * t2 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" T3 = T0 - (q0 - q3) * t3 * 3 / (0.4 * 4.18) * 0.3\n",
|
|
" T4 = T0 - (q0 - q4) * t4 * 3 / (0.4 * 4.18) * 0.25\n",
|
|
" \n",
|
|
" T5 = T4 + 2 * t5\n",
|
|
" \n",
|
|
" T40 = T5 + (q40 - q5 ) * t40 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" T30 = T40 + (q30 - q40) * t30 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" T20 = T30 + (q20 - q30) * t20 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" T10 = T20 + (q10 - q20) * t10 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" T00 = T10 + (q00 - q10) * t00 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" \n",
|
|
" TT1 = T00 + (qq1 - q00) * tt1 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" TT2 = TT1 + (qq2 - qq1) * tt2 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" TT3 = TT2 + (qq3 - qq2) * tt3 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" \n",
|
|
" TT20 = TT3 + (qq20 - qq3) * tt20 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" TT10 = TT20 + (qq10 - qq20) * tt10 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" \n",
|
|
" self.step_sizes = [0, t1, t2, t3, t4, t5, t40, t30, t20, t10, t00, tt1, tt2, tt3, tt20, tt10]\n",
|
|
" self.step_times = np.cumsum([0, t1, t2, t3, t4, t5, t40, t30, t20, t10, t00, tt1, tt2, tt3, tt20, tt10])\n",
|
|
" self.step_qs = [q0, q1, q2, q3, q4, q5, q40, q30, q20, q10, q00, qq1, qq2, qq3, qq20, qq10, q0]\n",
|
|
" \n",
|
|
" \n",
|
|
" \n",
|
|
" self.step_temperatures = [T0, T1 , T2 , T3 , T4 , T5 , T40, T30, T20, T10, T00, TT1, TT2, TT3, TT2, TT1,]\n",
|
|
" \n",
|
|
" self.step_q_from_to = list(zip(self.step_qs[:-1], self.step_qs[1:]))\n",
|
|
" \n",
|
|
" for pair in zip(self.step_times, self.step_q_from_to):\n",
|
|
" print(pair)\n",
|
|
" \n",
|
|
" self.program = list(zip(self.step_times, self.step_q_from_to))\n",
|
|
" \n",
|
|
" self.drying_time = 24. / load\n",
|
|
" \n",
|
|
" self.aux_duration = (q0 * self.step_times[9] - (np.array(self.step_sizes)[:10] * np.array(self.step_qs)[:10]).sum()) / 2 / qq3\n",
|
|
"\n",
|
|
" def lowest_heat_duration (self):\n",
|
|
"\n",
|
|
" t = self.duration\n",
|
|
" t5 = t\n",
|
|
"\n",
|
|
" if t > 14 :\n",
|
|
" t5 = t - 6\n",
|
|
" elif t > 12 :\n",
|
|
" t5 = t - 5\n",
|
|
" elif t > 10 :\n",
|
|
" t5 = t - 4\n",
|
|
" elif t > 8 :\n",
|
|
" t5 = t - 3\n",
|
|
" elif t > 7 :\n",
|
|
" t5 = t - 2\n",
|
|
" elif t > 6 :\n",
|
|
" t5 = t - 1\n",
|
|
" elif t < 5 :\n",
|
|
" t5 = t + 1\n",
|
|
"\n",
|
|
" return t5\n",
|
|
"\n",
|
|
"duration = 16\n",
|
|
"start = 6\n",
|
|
"load = 81 / 66\n",
|
|
"T0 = 1212\n",
|
|
"q0 = 81\n",
|
|
"\n",
|
|
"cosp = CokeOvenServiceProgram(duration, start, load, T0, q0)\n",
|
|
"\n",
|
|
"from functools import reduce\n",
|
|
"program_arr = np.array(reduce(lambda x, y: x+y,[ [(t, q0), (t, q1)] for t, (q0, q1) in cosp.program]))\n",
|
|
"\n",
|
|
"import matplotlib.ticker \n",
|
|
"\n",
|
|
"plt.figure(figsize=(10, 4))\n",
|
|
"plt.plot(program_arr.T[0] * 60, program_arr.T[1])\n",
|
|
"ax = plt.gca()\n",
|
|
"ax.xaxis.set_major_locator(matplotlib.ticker.MultipleLocator(60))\n",
|
|
"ax.xaxis.set_minor_locator(matplotlib.ticker.MultipleLocator(20))\n",
|
|
"plt.xticks(np.arange(0, 60)*60, np.arange(0, 60), rotation=90)\n",
|
|
"# plt.xticks(rotation=90)\n",
|
|
"# plt.minorticks_on()\n",
|
|
"plt.grid()\n",
|
|
"plt.grid(b=True, which='minor', color='r', linestyle='--')\n",
|
|
"\n",
|
|
"plt.axvline((start)*60)\n",
|
|
"plt.axvline((start+duration)*60)\n",
|
|
"\n",
|
|
"plt.axvline((start+duration+cosp.drying_time)*60)\n",
|
|
"plt.axvline((start+duration+cosp.drying_time+cosp.aux_duration)*60)\n",
|
|
"\n",
|
|
"twin = plt.gca().twinx()\n",
|
|
"twin.plot(cosp.step_times * 60, cosp.step_temperatures, 'o:')\n",
|
|
"twin.set_ylim(1120, 1320)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "b56ace82",
|
|
"metadata": {},
|
|
"source": [
|
|
"# 온도 계산 개선 - 배터리 열용량 0.07 Gcal / Rev / 'C"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 37,
|
|
"id": "35f7f4af",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"(0.0, (81, 69.61621621621622))\n",
|
|
"(3.5, (69.61621621621622, 58.83157894736841))\n",
|
|
"(7.0, (58.83157894736841, 48.599999999999994))\n",
|
|
"(10.5, (48.599999999999994, 42.038999999999994))\n",
|
|
"(14.5, (42.038999999999994, 38.879999999999995))\n",
|
|
"(24.5, (38.879999999999995, 42.038999999999994))\n",
|
|
"(27.75, (42.038999999999994, 48.599999999999994))\n",
|
|
"(30.35, (48.599999999999994, 58.83157894736841))\n",
|
|
"(32.43, (58.83157894736841, 69.61621621621622))\n",
|
|
"(34.094, (69.61621621621622, 81))\n",
|
|
"(36.4668813559322, (81, 72.9))\n",
|
|
"(39.4668813559322, (72.9, 67.22999999999999))\n",
|
|
"(42.4668813559322, (67.22999999999999, 62.370000000000005))\n",
|
|
"(47.4668813559322, (62.370000000000005, 67.22999999999999))\n",
|
|
"(50.4668813559322, (67.22999999999999, 72.9))\n",
|
|
"(53.4668813559322, (72.9, 81))\n"
|
|
]
|
|
},
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"C:\\Users\\RIST\\AppData\\Local\\Temp\\ipykernel_94484\\1371208751.py:132: MatplotlibDeprecationWarning: The 'b' parameter of grid() has been renamed 'visible' since Matplotlib 3.5; support for the old name will be dropped two minor releases later.\n",
|
|
" plt.grid(b=True, which='minor', color='r', linestyle='--')\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"(1120.0, 1320.0)"
|
|
]
|
|
},
|
|
"execution_count": 37,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"application/vnd.jupyter.widget-view+json": {
|
|
"model_id": "83ec293487c64de89f17879aaa8de54d",
|
|
"version_major": 2,
|
|
"version_minor": 0
|
|
},
|
|
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",
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"\n",
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" <div style=\"display: inline-block;\">\n",
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" <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
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" Figure\n",
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" </div>\n",
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' width=1000.0/>\n",
|
|
" </div>\n",
|
|
" "
|
|
],
|
|
"text/plain": [
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"class CokeOvenServiceProgram:\n",
|
|
" \"\"\" as implemented in excel sheet provided \"\"\"\n",
|
|
" def __init__ (self, duration, start, load, T0, q0):\n",
|
|
" self.start = start\n",
|
|
" self.end = start + duration\n",
|
|
" self.duration = duration\n",
|
|
" self.load = load\n",
|
|
" self.T0 = T0\n",
|
|
" self.q0 = q0\n",
|
|
" \n",
|
|
" self.a = 0.6 - (self.duration - 4) * 0.01 # 최소 열량 / 최대 열량 비율\n",
|
|
" self.b = 6 + self.duration / 2 # 감급 시작에서 감급 완료까지 시간, 정수 -6 에서 감급 시작 정수 중간 시각에 감급 완료\n",
|
|
"\n",
|
|
" t5 = self.lowest_heat_duration()\n",
|
|
" q5 = self.q0 * self.a\n",
|
|
"\n",
|
|
" t1 = self.b / 4\n",
|
|
" t2 = self.b / 4\n",
|
|
" t3 = self.b / 4\n",
|
|
" t4 = self.b / 3.5\n",
|
|
"\n",
|
|
" t40 = 13 / 4\n",
|
|
" t30 = t40 * 0.8\n",
|
|
" t20 = t30 * 0.8\n",
|
|
" t10 = t20 * 0.8\n",
|
|
" t00 = self.b / 5.9\n",
|
|
"\n",
|
|
" tt1 = 3\n",
|
|
" tt2 = 3\n",
|
|
" tt3 = 5\n",
|
|
" tt20 = 3\n",
|
|
" tt10 = 3\n",
|
|
"\n",
|
|
" q1 = q0 - 1 * (q0 - q5) / 3.7 \n",
|
|
" q2 = q0 - 2 * (q0 - q5) / 3.8\n",
|
|
" q3 = q0 - 3 * (q0 - q5) / 3.9\n",
|
|
" q4 = q0 - 3.7 * (q0 - q5) / 4\n",
|
|
"\n",
|
|
" q40 = q4\n",
|
|
" q30 = q3\n",
|
|
" q20 = q2\n",
|
|
" q10 = q1\n",
|
|
" q00 = q0\n",
|
|
" \n",
|
|
" qq1 = q00 * 0.9\n",
|
|
" qq2 = q00 * 0.83\n",
|
|
" qq3 = q00 * 0.77\n",
|
|
" qq20 = qq2\n",
|
|
" qq10 = qq1\n",
|
|
" \n",
|
|
" T1 = T0 - (q0 - q1) / (0.07 * 4.184) * 0.6\n",
|
|
" T2 = T0 - (q0 - q2) / (0.07 * 4.184) * 0.6\n",
|
|
" T3 = T0 - (q0 - q3) / (0.07 * 4.184) * 0.6 \n",
|
|
" T4 = T0 - (q0 - q4) / (0.07 * 4.184) * 0.6\n",
|
|
" \n",
|
|
" T5 = T0 - (q0 - q5) / (0.07 * 4.184) * 0.6\n",
|
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" \n",
|
|
" T40 = T0 - (q0 - q4) / (0.07 * 4.184) * 0.6\n",
|
|
" T30 = T0 - (q0 - q30) / (0.07 * 4.184) * 0.6\n",
|
|
" T20 = T0 - (q0 - q20) / (0.07 * 4.184) * 0.6\n",
|
|
" T10 = T0 - (q0 - q10) / (0.07 * 4.184) * 0.6\n",
|
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" T00 = T0 - (q0 - q00) / (0.07 * 4.184) * 0.6\n",
|
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" \n",
|
|
" TT1 = T0 - (q0 - qq1) / (0.07 * 4.184) * 0.6\n",
|
|
" TT2 = T0 - (q0 - qq2) / (0.07 * 4.184) * 0.6\n",
|
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" TT3 = T0 - (q0 - qq3) / (0.07 * 4.184) * 0.6\n",
|
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" \n",
|
|
" TT20 = T0 - (q0 - qq20) / (0.07 * 4.184) * 0.6\n",
|
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" TT10 = T0 - (q0 - qq10) / (0.07 * 4.184) * 0.6\n",
|
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" \n",
|
|
" self.step_sizes = [0, t1, t2, t3, t4, t5, t40, t30, t20, t10, t00, tt1, tt2, tt3, tt20, tt10]\n",
|
|
" self.step_times = np.cumsum([0, t1, t2, t3, t4, t5, t40, t30, t20, t10, t00, tt1, tt2, tt3, tt20, tt10])\n",
|
|
" self.step_qs = [q0, q1, q2, q3, q4, q5, q40, q30, q20, q10, q00, qq1, qq2, qq3, qq20, qq10, q0]\n",
|
|
" \n",
|
|
" self.step_temperatures = [T0, T1 , T2 , T3 , T4 , T5 , T40, T30, T20, T10, T00, TT1, TT2, TT3, TT2, TT1,]\n",
|
|
" \n",
|
|
" self.step_q_from_to = list(zip(self.step_qs[:-1], self.step_qs[1:]))\n",
|
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" \n",
|
|
" for pair in zip(self.step_times, self.step_q_from_to):\n",
|
|
" print(pair)\n",
|
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" \n",
|
|
" self.program = list(zip(self.step_times, self.step_q_from_to))\n",
|
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" \n",
|
|
" self.drying_time = 24. / load\n",
|
|
" \n",
|
|
" self.aux_duration = (q0 * self.step_times[9] - (np.array(self.step_sizes)[:10] * np.array(self.step_qs)[:10]).sum()) / 2 / qq3\n",
|
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"\n",
|
|
" def lowest_heat_duration (self):\n",
|
|
"\n",
|
|
" t = self.duration\n",
|
|
" t5 = t\n",
|
|
"\n",
|
|
" if t > 14 :\n",
|
|
" t5 = t - 6\n",
|
|
" elif t > 12 :\n",
|
|
" t5 = t - 5\n",
|
|
" elif t > 10 :\n",
|
|
" t5 = t - 4\n",
|
|
" elif t > 8 :\n",
|
|
" t5 = t - 3\n",
|
|
" elif t > 7 :\n",
|
|
" t5 = t - 2\n",
|
|
" elif t > 6 :\n",
|
|
" t5 = t - 1\n",
|
|
" elif t < 5 :\n",
|
|
" t5 = t + 1\n",
|
|
"\n",
|
|
" return t5\n",
|
|
"\n",
|
|
"duration = 16\n",
|
|
"start = 6\n",
|
|
"load = 81 / 66\n",
|
|
"T0 = 1212\n",
|
|
"q0 = 81\n",
|
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"\n",
|
|
"cosp = CokeOvenServiceProgram(duration, start, load, T0, q0)\n",
|
|
"\n",
|
|
"from functools import reduce\n",
|
|
"program_arr = np.array(reduce(lambda x, y: x+y,[ [(t, q0), (t, q1)] for t, (q0, q1) in cosp.program]))\n",
|
|
"\n",
|
|
"import matplotlib.ticker \n",
|
|
"\n",
|
|
"plt.figure(figsize=(10, 4))\n",
|
|
"plt.plot(program_arr.T[0] * 60, program_arr.T[1])\n",
|
|
"ax = plt.gca()\n",
|
|
"ax.xaxis.set_major_locator(matplotlib.ticker.MultipleLocator(60))\n",
|
|
"ax.xaxis.set_minor_locator(matplotlib.ticker.MultipleLocator(20))\n",
|
|
"plt.xticks(np.arange(0, 60)*60, np.arange(0, 60), rotation=90)\n",
|
|
"# plt.xticks(rotation=90)\n",
|
|
"# plt.minorticks_on()\n",
|
|
"plt.grid()\n",
|
|
"plt.grid(b=True, which='minor', color='r', linestyle='--')\n",
|
|
"\n",
|
|
"plt.axvline((start)*60)\n",
|
|
"plt.axvline((start+duration)*60)\n",
|
|
"\n",
|
|
"plt.axvline((start+duration+cosp.drying_time)*60)\n",
|
|
"plt.axvline((start+duration+cosp.drying_time+cosp.aux_duration)*60)\n",
|
|
"\n",
|
|
"twin = plt.gca().twinx()\n",
|
|
"twin.plot(cosp.step_times * 60, cosp.step_temperatures, 'o:')\n",
|
|
"twin.set_ylim(1120, 1320)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 38,
|
|
"id": "01cba2bf",
|
|
"metadata": {
|
|
"scrolled": false
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"160.4006440677966"
|
|
]
|
|
},
|
|
"execution_count": 38,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"np.sum(np.array(cosp.step_sizes) * 60 / 20)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 39,
|
|
"id": "417a4faf",
|
|
"metadata": {
|
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"scrolled": false
|
|
},
|
|
"outputs": [
|
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{
|
|
"data": {
|
|
"text/plain": [
|
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"159.0"
|
|
]
|
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},
|
|
"execution_count": 39,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"np.sum(np.round(np.array(cosp.step_sizes) * 60 / 20))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 40,
|
|
"id": "4ac4926b",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([ 0., 10., 10., 10., 12., 30., 10., 8., 6., 5., 7., 9., 9.,\n",
|
|
" 15., 9., 9.])"
|
|
]
|
|
},
|
|
"execution_count": 40,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"np.round(np.array(cosp.step_sizes) * 60 / 20)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 41,
|
|
"id": "58fb00cb",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([[ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
|
|
" [ 1.05000000e+01, 1.00000000e+01, 5.00000000e-01],\n",
|
|
" [ 1.05000000e+01, 1.00000000e+01, 5.00000000e-01],\n",
|
|
" [ 1.05000000e+01, 1.00000000e+01, 5.00000000e-01],\n",
|
|
" [ 1.20000000e+01, 1.20000000e+01, 0.00000000e+00],\n",
|
|
" [ 3.00000000e+01, 3.00000000e+01, 0.00000000e+00],\n",
|
|
" [ 9.75000000e+00, 1.00000000e+01, -2.50000000e-01],\n",
|
|
" [ 7.80000000e+00, 8.00000000e+00, -2.00000000e-01],\n",
|
|
" [ 6.24000000e+00, 6.00000000e+00, 2.40000000e-01],\n",
|
|
" [ 4.99200000e+00, 5.00000000e+00, -8.00000000e-03],\n",
|
|
" [ 7.11864407e+00, 7.00000000e+00, 1.18644068e-01],\n",
|
|
" [ 9.00000000e+00, 9.00000000e+00, 0.00000000e+00],\n",
|
|
" [ 9.00000000e+00, 9.00000000e+00, 0.00000000e+00],\n",
|
|
" [ 1.50000000e+01, 1.50000000e+01, 0.00000000e+00],\n",
|
|
" [ 9.00000000e+00, 9.00000000e+00, 0.00000000e+00],\n",
|
|
" [ 9.00000000e+00, 9.00000000e+00, 0.00000000e+00]])"
|
|
]
|
|
},
|
|
"execution_count": 41,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"np.array(list(zip(np.array(cosp.step_sizes) * 60 / 20,\n",
|
|
"np.round(np.array(cosp.step_sizes) * 60 / 20),\n",
|
|
"np.array(cosp.step_sizes) * 60 / 20 - np.round(np.array(cosp.step_sizes) * 60 / 20))))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 42,
|
|
"id": "2d1a860e",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"C:\\Users\\RIST\\AppData\\Local\\Temp\\ipykernel_94484\\1001734892.py:1: RuntimeWarning: invalid value encountered in true_divide\n",
|
|
" 100 * (np.array(cosp.step_sizes) * 60 / 20 - np.round(np.array(cosp.step_sizes) * 60 / 20)) / (np.array(cosp.step_sizes) * 60 / 20)\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([ nan, 4.76190476, 4.76190476, 4.76190476, 0. ,\n",
|
|
" 0. , -2.56410256, -2.56410256, 3.84615385, -0.16025641,\n",
|
|
" 1.66666667, 0. , 0. , 0. , 0. ,\n",
|
|
" 0. ])"
|
|
]
|
|
},
|
|
"execution_count": 42,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"100 * (np.array(cosp.step_sizes) * 60 / 20 - np.round(np.array(cosp.step_sizes) * 60 / 20)) / (np.array(cosp.step_sizes) * 60 / 20)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "51b40602",
|
|
"metadata": {},
|
|
"source": [
|
|
"# 열량 증감 시점을 리버스 간격과 정렬"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 43,
|
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"id": "0fa97f83",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"(0.0, (81.0, 69.61621621621622))\n",
|
|
"(3.3333333333333335, (69.61621621621622, 58.83157894736841))\n",
|
|
"(6.666666666666667, (58.83157894736841, 48.599999999999994))\n",
|
|
"(10.0, (48.599999999999994, 42.038999999999994))\n",
|
|
"(14.0, (42.038999999999994, 38.879999999999995))\n",
|
|
"(24.0, (38.879999999999995, 42.038999999999994))\n",
|
|
"(27.333333333333332, (42.038999999999994, 48.599999999999994))\n",
|
|
"(30.0, (48.599999999999994, 58.83157894736841))\n",
|
|
"(32.0, (58.83157894736841, 69.61621621621622))\n",
|
|
"(33.666666666666664, (69.61621621621622, 81.0))\n",
|
|
"(36.0, (81.0, 72.9))\n",
|
|
"(39.0, (72.9, 67.22999999999999))\n",
|
|
"(42.0, (67.22999999999999, 62.370000000000005))\n",
|
|
"(47.0, (62.370000000000005, 67.22999999999999))\n",
|
|
"(50.0, (67.22999999999999, 72.9))\n",
|
|
"(53.0, (72.9, 81.0))\n"
|
|
]
|
|
},
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"C:\\Users\\RIST\\AppData\\Local\\Temp\\ipykernel_94484\\4051397401.py:170: MatplotlibDeprecationWarning: The 'b' parameter of grid() has been renamed 'visible' since Matplotlib 3.5; support for the old name will be dropped two minor releases later.\n",
|
|
" plt.grid(b=True, which='minor', color='r', linestyle='--')\n"
|
|
]
|
|
},
|
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{
|
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"data": {
|
|
"text/plain": [
|
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"(1120.0, 1320.0)"
|
|
]
|
|
},
|
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"execution_count": 43,
|
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"metadata": {},
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"output_type": "execute_result"
|
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},
|
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{
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"data": {
|
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"application/vnd.jupyter.widget-view+json": {
|
|
"model_id": "f99979c47ffe4ef1a68dc176a4b61be9",
|
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"version_major": 2,
|
|
"version_minor": 0
|
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},
|
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"image/png": 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Hj4darRbdCcORGDnrcsb2ydknjuMQHR0Ng8EgeHAch7i4OBgMBowdO7ZPYpTePmfsEwAEBQXxP+mrq6tDUFAQAgMDkZycjJCQEHh7e6OqqqrHmMDAwHvGOBqn5BiiTDRBJ4T0GUfucy9XjNLb54x9Sk9PR2pqKpqamlBTU4NJkyZBr9fzt2+SmsA5EiNnXc7YPjn7lJCQgEWLFgGwXAvDx8cHRqORLzcajUhOTr7vGDnrcsb2ydmnvLw8yVuU9nTxLLlilN4+Z+wTILxuQkZGBgwGA5qbmwFYboOWmpqKqVOn3neMnHXJ2SeiPDRBJ4T0mZ7uQ9r1fqR9EaP09jljnwYNGoSKigrBtjlz5iAsLAynTp2SnMA5EiNnXc7YPjn71PUWmJ2dnVCr1YLbclVWVoquSuxIjJx1OWP75OwTABw5cgRDhw7FggUL+Isg3msSJ1eM0tvnjH3qOjGVmuBLXSXdkRg565KzT0R5VH39FXtCyP+voKAgtmXLFmY2myUfZWVlfRaj9PY5Y59aWlpEF4gqLCxkaWlpLCkpiZ08efKBxMhZlzO2T84+daVSqZhWq2UDBgzgt3l5ebHr168/0Bg563LG9snRp7i4OFZaWsqamppYbGwsq6ysZBzH9fj6csUovX3O2CfGGL9PW1ub6JosAQEBrKmp6YHEyFmXnH0iykITdEJIn4mNjbU5kWTMcqBBtxtNyBWj9PY5Y58iIyPZsWPHRPuuXLmSTZ48maWlpYnKHImRsy5nbJ+cfdLpdKy2tpZ/fujQIRYWFsY/P3v2LAsKCrrvGDnrcsb2ydknK09PT7ZhwwZmNBpZcnIy6+zslNyvL2KU3j5n7NP48ePZ448/zm7cuCFa7Pvvv/+Yn5/fA4mRsy45+0SUha7iTgjpM++88w5rbm62WT5kyBC2d+/ePolRevucsU9TpkxhxcXF7NVXXxXt/8033zCz2cxWrVp13zFy1uWM7ZOzT7NnzxYMzkeMGCEoN5lMoqt8OxIjZ13O2D45+9RdRkYGGz16NCstLe31ra3kilF6+5ylT7m5uYLn/fr1Ezzfvn07e/rpp+87Rs665OwTUR66DzohhBBCCCGEEKIA9BV3QgghhBBCCCFEAWiCTgghhBBCCCGEKABN0AkhhBBCCCGEEAWgCTohhBBCCCGEEKIANEEnhBBCCCGEEEIUgCbohBBCCCGEEEKIAtAEnRBCCCGEEEIIUQCaoBNCCCGEEEIIIQpAE3RCCCGEEEIIIUQBaIJOCCGEEEIIIYQoAE3QCSGEEEIIIYQQBaAJOiGEEEIIIYQQogA0QSeEEEIIIYQQQhSAJuiEEEIIIYQQQogC0ASdEEIIIYQQQghRgP8B11dtNen20MYAAAAASUVORK5CYII=",
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" <div style=\"display: inline-block;\">\n",
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" <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
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" Figure\n",
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" </div>\n",
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" <img 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' 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" </div>\n",
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" "
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],
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"text/plain": [
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"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"class CokeOvenServiceProgram:\n",
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" \"\"\" as implemented in excel sheet provided \"\"\"\n",
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" def __init__ (self, duration, start, load, T0, q0):\n",
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" self.start = start\n",
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" self.end = start + duration\n",
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" self.duration = duration\n",
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" self.load = load\n",
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" self.T0 = T0\n",
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" self.q0 = q0\n",
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" \n",
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" self.a = 0.6 - (self.duration - 4) * 0.01 # 최소 열량 / 최대 열량 비율\n",
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" self.b = 6 + self.duration / 2 # 감급 시작에서 감급 완료까지 시간, 정수 -6 에서 감급 시작 정수 중간 시각에 감급 완료\n",
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"\n",
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" t5 = self.lowest_heat_duration()\n",
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" q5 = self.q0 * self.a\n",
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"\n",
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" t1 = self.b / 4\n",
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" t2 = self.b / 4\n",
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" t3 = self.b / 4\n",
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" t4 = self.b / 3.5\n",
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"\n",
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" t40 = 13 / 4\n",
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" t30 = t40 * 0.8\n",
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" t20 = t30 * 0.8\n",
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" t10 = t20 * 0.8\n",
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" t00 = self.b / 5.9\n",
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"\n",
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" tt1 = 3\n",
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" tt2 = 3\n",
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" tt3 = 5\n",
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" tt20 = 3\n",
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" tt10 = 3\n",
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"\n",
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" q1 = q0 - 1 * (q0 - q5) / 3.7 \n",
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" q2 = q0 - 2 * (q0 - q5) / 3.8\n",
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" q3 = q0 - 3 * (q0 - q5) / 3.9\n",
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" q4 = q0 - 3.7 * (q0 - q5) / 4\n",
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"\n",
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" q40 = q4\n",
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" q30 = q3\n",
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" q20 = q2\n",
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" q10 = q1\n",
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" q00 = q0\n",
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" \n",
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" qq1 = q00 * 0.9\n",
|
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" qq2 = q00 * 0.83\n",
|
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" qq3 = q00 * 0.77\n",
|
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" qq20 = qq2\n",
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" qq10 = qq1\n",
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" \n",
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" T1 = T0 - (q0 - q1) / (0.07 * 4.184) * 0.6\n",
|
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" T2 = T0 - (q0 - q2) / (0.07 * 4.184) * 0.6\n",
|
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" T3 = T0 - (q0 - q3) / (0.07 * 4.184) * 0.6 \n",
|
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" T4 = T0 - (q0 - q4) / (0.07 * 4.184) * 0.6\n",
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" \n",
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" T5 = T0 - (q0 - q5) / (0.07 * 4.184) * 0.6\n",
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" \n",
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" T40 = T0 - (q0 - q4) / (0.07 * 4.184) * 0.6\n",
|
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" T30 = T0 - (q0 - q30) / (0.07 * 4.184) * 0.6\n",
|
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" T20 = T0 - (q0 - q20) / (0.07 * 4.184) * 0.6\n",
|
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" T10 = T0 - (q0 - q10) / (0.07 * 4.184) * 0.6\n",
|
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" T00 = T0 - (q0 - q00) / (0.07 * 4.184) * 0.6\n",
|
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" \n",
|
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" TT1 = T0 - (q0 - qq1) / (0.07 * 4.184) * 0.6\n",
|
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" TT2 = T0 - (q0 - qq2) / (0.07 * 4.184) * 0.6\n",
|
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" TT3 = T0 - (q0 - qq3) / (0.07 * 4.184) * 0.6\n",
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" \n",
|
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" TT20 = T0 - (q0 - qq20) / (0.07 * 4.184) * 0.6\n",
|
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" TT10 = T0 - (q0 - qq10) / (0.07 * 4.184) * 0.6\n",
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" \n",
|
|
" self.step_sizes = [0, t1, t2, t3, t4, t5, t40, t30, t20, t10, t00, tt1, tt2, tt3, tt20, tt10]\n",
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" \n",
|
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" self.step_sizes = np.round(np.array(self.step_sizes) * 60 / 20) / 3\n",
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" \n",
|
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" self.step_times = np.cumsum([0, t1, t2, t3, t4, t5, t40, t30, t20, t10, t00, tt1, tt2, tt3, tt20, tt10])\n",
|
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" self.step_times = np.cumsum(self.step_sizes)\n",
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" \n",
|
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" self.step_qs = np.array([q0, q1, q2, q3, q4, q5, q40, q30, q20, q10, q00, qq1, qq2, qq3, qq20, qq10, q0])\n",
|
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" \n",
|
|
" self.step_temperatures = [T0, T1 , T2 , T3 , T4 , T5 , T40, T30, T20, T10, T00, TT1, TT2, TT3, TT2, TT1,]\n",
|
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" \n",
|
|
" if False: # use_old_temperature:\n",
|
|
" self.step_temperatures = self.calculate_temperatues_old()\n",
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|
" \n",
|
|
" self.step_q_from_to = list(zip(self.step_qs[:-1], self.step_qs[1:]))\n",
|
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" \n",
|
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" for pair in zip(self.step_times, self.step_q_from_to):\n",
|
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" print(pair)\n",
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" \n",
|
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" self.program = list(zip(self.step_times, self.step_q_from_to))\n",
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" \n",
|
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" self.drying_time = 24. / load\n",
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" \n",
|
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" self.aux_duration = (q0 * self.step_times[9] - (self.step_sizes.ravel()[:10] * self.step_qs[:10]).sum()) / 2 / qq3\n",
|
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"\n",
|
|
" def lowest_heat_duration (self):\n",
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"\n",
|
|
" t = self.duration\n",
|
|
" t5 = t\n",
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|
"\n",
|
|
" if t > 14 :\n",
|
|
" t5 = t - 6\n",
|
|
" elif t > 12 :\n",
|
|
" t5 = t - 5\n",
|
|
" elif t > 10 :\n",
|
|
" t5 = t - 4\n",
|
|
" elif t > 8 :\n",
|
|
" t5 = t - 3\n",
|
|
" elif t > 7 :\n",
|
|
" t5 = t - 2\n",
|
|
" elif t > 6 :\n",
|
|
" t5 = t - 1\n",
|
|
" elif t < 5 :\n",
|
|
" t5 = t + 1\n",
|
|
"\n",
|
|
" return t5\n",
|
|
" \n",
|
|
" def calculate_temperatues_old (self):\n",
|
|
" t0, t1, t2, t3, t4, t5, t40, t30, t20, t10, t00, tt1, tt2, tt3, tt20, tt10 = self.step_sizes\n",
|
|
" q0, q1, q2, q3, q4, q5, q40, q30, q20, q10, q00, qq1, qq2, qq3, qq20, qq10, qq00 = self.step_qs\n",
|
|
" \n",
|
|
" T0 = self.T0\n",
|
|
" \n",
|
|
" T1 = T0 - (q0 - q1) * t1 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" T2 = T0 - (q0 - q2) * t2 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" T3 = T0 - (q0 - q3) * t3 * 3 / (0.4 * 4.18) * 0.3\n",
|
|
" T4 = T0 - (q0 - q4) * t4 * 3 / (0.4 * 4.18) * 0.25\n",
|
|
" \n",
|
|
" T5 = T4 + 2 * t5\n",
|
|
" \n",
|
|
" T40 = T5 + (q40 - q5 ) * t40 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" T30 = T40 + (q30 - q40) * t30 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" T20 = T30 + (q20 - q30) * t20 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" T10 = T20 + (q10 - q20) * t10 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" T00 = T10 + (q00 - q10) * t00 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" \n",
|
|
" TT1 = T00 + (qq1 - q00) * tt1 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" TT2 = TT1 + (qq2 - qq1) * tt2 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" TT3 = TT2 + (qq3 - qq2) * tt3 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" \n",
|
|
" TT20 = TT3 + (qq20 - qq3) * tt20 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" TT10 = TT20 + (qq10 - qq20) * tt10 * 3 / (0.4 * 4.18) * 0.33\n",
|
|
" \n",
|
|
" return [T0, T1 , T2 , T3 , T4 , T5 , T40, T30, T20, T10, T00, TT1, TT2, TT3, TT2, TT1,]\n",
|
|
"\n",
|
|
"duration = 16\n",
|
|
"start = 6\n",
|
|
"load = 81 / 66\n",
|
|
"T0 = 1212\n",
|
|
"q0 = 81\n",
|
|
"\n",
|
|
"cosp = CokeOvenServiceProgram(duration, start, load, T0, q0)\n",
|
|
"cosp.step_temperatures = cosp.calculate_temperatues_old()\n",
|
|
"\n",
|
|
"from functools import reduce\n",
|
|
"\n",
|
|
"program_arr = np.array(reduce(lambda x, y: x+y,[ [(t, q0), (t, q1)] for t, (q0, q1) in cosp.program]))\n",
|
|
"\n",
|
|
"import matplotlib.ticker \n",
|
|
"\n",
|
|
"plt.figure(figsize=(10, 4))\n",
|
|
"plt.plot(program_arr.T[0] * 60, program_arr.T[1])\n",
|
|
"ax = plt.gca()\n",
|
|
"ax.xaxis.set_major_locator(matplotlib.ticker.MultipleLocator(60))\n",
|
|
"ax.xaxis.set_minor_locator(matplotlib.ticker.MultipleLocator(20))\n",
|
|
"plt.xticks(np.arange(0, 60)*60, np.arange(0, 60), rotation=90)\n",
|
|
"# plt.xticks(rotation=90)\n",
|
|
"# plt.minorticks_on()\n",
|
|
"plt.grid()\n",
|
|
"plt.grid(b=True, which='minor', color='r', linestyle='--')\n",
|
|
"\n",
|
|
"plt.axvline((start)*60)\n",
|
|
"plt.axvline((start+duration)*60)\n",
|
|
"\n",
|
|
"plt.axvline((start+duration+cosp.drying_time)*60)\n",
|
|
"plt.axvline((start+duration+cosp.drying_time+cosp.aux_duration)*60)\n",
|
|
"\n",
|
|
"twin = plt.gca().twinx()\n",
|
|
"twin.plot(cosp.step_times * 60, cosp.step_temperatures, 'o:')\n",
|
|
"twin.set_ylim(1120, 1320)"
|
|
]
|
|
}
|
|
],
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.12"
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},
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"toc": {
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"nav_menu": {},
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"title_cell": "Table of Contents",
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"title_sidebar": "Contents",
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