diff --git a/CokeOvenServiceSimulator.ipynb b/CokeOvenServiceSimulator.ipynb index 509a6b5..887a8bd 100644 --- a/CokeOvenServiceSimulator.ipynb +++ b/CokeOvenServiceSimulator.ipynb @@ -11,6 +11,14 @@ "%matplotlib widget" ] }, + { + "cell_type": "markdown", + "id": "9fb0a4f4", + "metadata": {}, + "source": [ + "# 코크 오븐 모델" + ] + }, { "cell_type": "code", "execution_count": 2, @@ -74,15 +82,16 @@ " else:\n", " self.t_last = self.t\n", " \n", - " self.push_and_charge(CokeCharge(self.t_last))\n", + " self.push_and_charge(CokeCharge(self.t_last, self.))\n", " self.t += dt\n", " \n", "\n", "class CokeCharge:\n", " \n", - " def __init__ (self, t_charge):\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", @@ -203,7 +212,7 @@ { "data": { "text/plain": [ - "[]" + "[]" ] }, "execution_count": 5, @@ -213,7 +222,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "31df4c517e764ddf820efaa37ae44ead", + "model_id": "c35cc72fb85446a289a617eb2e40d9f8", "version_major": 2, "version_minor": 0 }, @@ -251,7 +260,7 @@ { "data": { "text/plain": [ - "[]" + "[]" ] }, "execution_count": 6, @@ -261,7 +270,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6a7fc82d4ca64a47be2bacb5cd186e9d", + "model_id": "6818908e9143471298fb95dbc493e841", "version_major": 2, "version_minor": 0 }, @@ -361,7 +370,7 @@ { "data": { "text/plain": [ - "[]" + "[]" ] }, "execution_count": 11, @@ -371,7 +380,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "a96ccf235bd149df92dee4920c267e94", + "model_id": "48707ff799f947d3a7885e03af2728f5", "version_major": 2, "version_minor": 0 }, @@ -402,7 +411,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "id": "235b5f6e", "metadata": {}, "outputs": [ @@ -553,7 +562,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, "id": "99d40063", "metadata": {}, "outputs": [ @@ -641,7 +650,13 @@ "Push timing within this time step. 0.30370370370285116 since last P/C. P/C interval = 0.2962962962962963\n", "Push timing within this time step. 0.3074074074065365 since last P/C. P/C interval = 0.2962962962962963\n", "Push timing within this time step. 0.3111111111102218 since last P/C. P/C interval = 0.2962962962962963\n", - "Push timing within this time step. 0.29814814814724144 since last P/C. P/C interval = 0.2962962962962963\n", + "Push timing within this time step. 0.29814814814724144 since last P/C. P/C interval = 0.2962962962962963\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Push timing within this time step. 0.3018518518509268 since last P/C. P/C interval = 0.2962962962962963\n", "Push timing within this time step. 0.3055555555546121 since last P/C. P/C interval = 0.2962962962962963\n", "Push timing within this time step. 0.30925925925829745 since last P/C. P/C interval = 0.2962962962962963\n", @@ -755,16 +770,16 @@ "Push timing within this time step. 0.3018518518501878 since last P/C. P/C interval = 0.2962962962962963\n", "Push timing within this time step. 0.30555555555388025 since last P/C. P/C interval = 0.2962962962962963\n", "Push timing within this time step. 0.3092592592575727 since last P/C. P/C interval = 0.2962962962962963\n", - "Push timing within this time step. 0.31296296296126513 since last P/C. P/C interval = 0.2962962962962963\n" + "Push timing within this time step. 0.31296296296126513 since last P/C. P/C interval = 0.2962962962962963\n", + "Push timing within this time step. 0.29999999999829186 since last P/C. P/C interval = 0.2962962962962963\n", + "Push timing within this time step. 0.3037037037019843 since last P/C. P/C interval = 0.2962962962962963\n", + "Push timing within this time step. 0.30740740740567674 since last P/C. P/C interval = 0.2962962962962963\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Push timing within this time step. 0.29999999999829186 since last P/C. P/C interval = 0.2962962962962963\n", - "Push timing within this time step. 0.3037037037019843 since last P/C. P/C interval = 0.2962962962962963\n", - "Push timing within this time step. 0.30740740740567674 since last P/C. P/C interval = 0.2962962962962963\n", "Push timing within this time step. 0.3111111111093692 since last P/C. P/C interval = 0.2962962962962963\n", "Push timing within this time step. 0.2981481481463959 since last P/C. P/C interval = 0.2962962962962963\n", "Push timing within this time step. 0.30185185185008834 since last P/C. P/C interval = 0.2962962962962963\n", @@ -828,7 +843,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "id": "a86acbef", "metadata": {}, "outputs": [ @@ -1091,7 +1106,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "id": "1179dfeb", "metadata": {}, "outputs": [ @@ -1116,7 +1131,7 @@ " 62.29 , 67.54 , 67.54 , 73. , 73. ]])" ] }, - "execution_count": 16, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -1127,7 +1142,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "id": "3ed23b12", "metadata": { "scrolled": false @@ -1136,7 +1151,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ba49f91237814f169a176fff3296fb64", + "model_id": "3a000d6091a64ed1b41b010d5bfa68b7", "version_major": 2, "version_minor": 0 }, @@ -1179,7 +1194,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 17, "id": "4df78f65", "metadata": {}, "outputs": [ @@ -1189,7 +1204,7 @@ "1425.6" ] }, - "execution_count": 18, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -1200,7 +1215,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 18, "id": "2065d0c6", "metadata": {}, "outputs": [], @@ -1244,7 +1259,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 19, "id": "315b9960", "metadata": {}, "outputs": [], @@ -1287,24 +1302,24 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 20, "id": "85cbc85b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 21, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0c31665b58574d3796702f44e72b881e", + "model_id": "8e511c005c0e4f42add861b4a57c743c", "version_major": 2, "version_minor": 0 }, @@ -1337,7 +1352,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 21, "id": "1ea1b3e5", "metadata": {}, "outputs": [], @@ -1353,7 +1368,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 22, "id": "245eff1f", "metadata": {}, "outputs": [], @@ -1385,7 +1400,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 23, "id": "d79e655e", "metadata": {}, "outputs": [ @@ -1404,7 +1419,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 24, "id": "1a04c477", "metadata": {}, "outputs": [ @@ -1414,7 +1429,7 @@ "(5, 3)" ] }, - "execution_count": 25, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -1429,7 +1444,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 25, "id": "51040443", "metadata": {}, "outputs": [ @@ -1454,7 +1469,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 26, "id": "37535ff4", "metadata": { "scrolled": false @@ -1463,7 +1478,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "09cfa23944d24b61ba8492dd35b64c00", + "model_id": "743317202bad481198792b8fe3eea6b0", "version_major": 2, "version_minor": 0 }, @@ -1505,7 +1520,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 27, "id": "32f3b457", "metadata": {}, "outputs": [ @@ -1535,7 +1550,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\RIST\\AppData\\Local\\Temp\\ipykernel_16724\\1711604546.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", + "C:\\Users\\RIST\\AppData\\Local\\Temp\\ipykernel_75396\\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" ] }, @@ -1545,14 +1560,14 @@ "(1120.0, 1320.0)" ] }, - "execution_count": 29, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6e0522b1e0e54a028e98779e53faa3fc", + "model_id": "5afeca3240394fc7978059e3124fd058", "version_major": 2, "version_minor": 0 }, @@ -1732,7 +1747,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 28, "id": "35f7f4af", "metadata": {}, "outputs": [ @@ -1762,7 +1777,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\RIST\\AppData\\Local\\Temp\\ipykernel_16724\\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", + "C:\\Users\\RIST\\AppData\\Local\\Temp\\ipykernel_75396\\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" ] }, @@ -1772,14 +1787,14 @@ "(1120.0, 1320.0)" ] }, - "execution_count": 30, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4af505b882a34797a4fbb34822959ed8", + "model_id": "29aac9776eec4aa6a8c8b592295eec06", "version_major": 2, "version_minor": 0 }, @@ -1949,7 +1964,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 29, "id": "01cba2bf", "metadata": { "scrolled": false @@ -1961,7 +1976,7 @@ "160.4006440677966" ] }, - "execution_count": 31, + "execution_count": 29, "metadata": {}, "output_type": "execute_result" } @@ -1972,7 +1987,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 30, "id": "417a4faf", "metadata": { "scrolled": false @@ -1984,7 +1999,7 @@ "159.0" ] }, - "execution_count": 32, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" } @@ -1995,7 +2010,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 31, "id": "4ac4926b", "metadata": {}, "outputs": [ @@ -2006,7 +2021,7 @@ " 15., 9., 9.])" ] }, - "execution_count": 39, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -2017,7 +2032,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 32, "id": "58fb00cb", "metadata": {}, "outputs": [ @@ -2042,7 +2057,7 @@ " [ 9.00000000e+00, 9.00000000e+00, 0.00000000e+00]])" ] }, - "execution_count": 33, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } @@ -2055,7 +2070,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 33, "id": "2d1a860e", "metadata": {}, "outputs": [ @@ -2063,7 +2078,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\RIST\\AppData\\Local\\Temp\\ipykernel_16724\\1001734892.py:1: RuntimeWarning: invalid value encountered in true_divide\n", + "C:\\Users\\RIST\\AppData\\Local\\Temp\\ipykernel_75396\\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" ] }, @@ -2076,7 +2091,7 @@ " 0. ])" ] }, - "execution_count": 34, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } @@ -2095,7 +2110,7 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 34, "id": "0fa97f83", "metadata": {}, "outputs": [ @@ -2125,7 +2140,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\RIST\\AppData\\Local\\Temp\\ipykernel_16724\\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", + "C:\\Users\\RIST\\AppData\\Local\\Temp\\ipykernel_75396\\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" ] }, @@ -2135,14 +2150,14 @@ "(1120.0, 1320.0)" ] }, - "execution_count": 48, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "560d90bd0ae24e6d9d801a0d850dbffd", + "model_id": "890645dddab24b1f96dde74b2cddb099", "version_major": 2, "version_minor": 0 }, @@ -2350,75 +2365,285 @@ }, { "cell_type": "markdown", - "id": "889c6940", + "id": "fd1817d3", "metadata": {}, "source": [ - "# 추가감산 감급 없이" + "# 탄화실 나이 분포" + ] + }, + { + "cell_type": "markdown", + "id": "9c64324b", + "metadata": {}, + "source": [ + "## 장입-추출 시퀀스\n", + "\n", + "$n$ 번 건류실 추출/장입 후 $n+5$ 번 건류실에 추출/장입\n", + "* 1 번에서 시작시 66번까지 진행 이후 3 번에서 시작. $ 1, 6, 11, \\ldots , 66 $\n", + "* 3 번에서 63번까지 진행 이후 5 번에서 시작. $ 3, 6, 11, \\ldots , 63 $\n", + "* 5 번에서 65번까지 진행 이후 2 번에서 시작. $ 5, 6, 11, \\ldots , 65 $\n", + "* 2 번에서 62번까지 진행 이후 4 번에서 시작. $ 2, 6, 11, \\ldots , 62 $\n", + "* 4 번에서 64번까지 진행 이후 다시 1 번에서 시작. $ 4, 9, 14, \\ldots , 64 $\n" + ] + }, + { + "cell_type": "markdown", + "id": "de03e1d6", + "metadata": {}, + "source": [ + "### 탄화실 별 장입 시기" ] }, { "cell_type": "code", - "execution_count": 54, - "id": "07c3818c", + "execution_count": 35, + "id": "99dd258f", + "metadata": {}, + "outputs": [], + "source": [ + "n_oven = 66\n", + "\n", + "oven_idx_sequence = np.zeros(n_oven)\n", + "\n", + "start_indices = [1, 3, 5, 2, 4]\n", + "\n", + "i_order = 0\n", + "for idx0 in np.array(start_indices)-1:\n", + " for idx in range(idx0, n_oven, 5):\n", + " oven_idx_sequence[idx] = i_order\n", + " i_order += 1" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "125f87b0", "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(0.0, (81.0, 70.4918918918919))\n", - "(3.0, (70.4918918918919, 60.53684210526316))\n", - "(6.0, (60.53684210526316, 51.0923076923077))\n", - "(9.0, (51.0923076923077, 45.036))\n", - "(12.333333333333334, (45.036, 42.120000000000005))\n", - "(20.333333333333336, (42.120000000000005, 45.036))\n", - "(27.000000000000004, (45.036, 51.0923076923077))\n", - "(35.0, (51.0923076923077, 60.53684210526316))\n", - "(45.0, (60.53684210526316, 70.4918918918919))\n", - "(57.666666666666664, (70.4918918918919, 81.0))\n", - "(59.666666666666664, (81.0, 72.9))\n", - "(62.666666666666664, (72.9, 67.22999999999999))\n", - "(65.66666666666666, (67.22999999999999, 62.370000000000005))\n", - "(70.66666666666666, (62.370000000000005, 67.22999999999999))\n", - "(73.66666666666666, (67.22999999999999, 72.9))\n", - "(76.66666666666666, (72.9, 81.0))\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\RIST\\AppData\\Local\\Temp\\ipykernel_16724\\3299767158.py:161: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n", - " plt.figure(figsize=(10, 4))\n", - "C:\\Users\\RIST\\AppData\\Local\\Temp\\ipykernel_16724\\3299767158.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" - ] - }, { "data": { "text/plain": [ - "(-60.0, 3540.0)" + "" ] }, - "execution_count": 54, + "execution_count": 37, "metadata": {}, "output_type": "execute_result" }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6be7e273c1e440f795c00e9ed06b1073", + "model_id": "640e10056e1c4fdebf56e839d1792454", "version_major": 2, "version_minor": 0 }, - "image/png": 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", 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"3fc5bccd", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 2, 7, 12,\n", + " 17, 22, 27, 32, 37, 42, 47, 52, 57, 62, 4, 9, 14, 19, 24, 29, 34,\n", + " 39, 44, 49, 54, 59, 64, 1, 6, 11, 16, 21, 26, 31, 36, 41, 46, 51,\n", + " 56, 61, 3, 8, 13, 18, 23, 28, 33, 38, 43, 48, 53, 58, 63])" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "oven_idx_order" + ] + }, + { + "cell_type": "markdown", + "id": "07a399f4", + "metadata": {}, + "source": [ + "# Coke Charge 에 탄화실 번호 부여" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "9ce8fc25", + "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, 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\n", + "
\n", + " Figure\n", + "
\n", + " \n", "
\n", " " ], @@ -2452,10 +2677,10 @@ " t3 = self.b / 4\n", " t4 = self.b / 3.5\n", "\n", - " t40 = 13 / 4 * 2\n", - " t30 = t40 / 0.8\n", - " t20 = t30 / 0.8\n", - " t10 = t20 / 0.8\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", @@ -2576,7 +2801,7 @@ " \n", " return [T0, T1 , T2 , T3 , T4 , T5 , T40, T30, T20, T10, T00, TT1, TT2, TT3, TT2, TT1,]\n", "\n", - "duration = 12\n", + "duration = 16\n", "start = 6\n", "load = 81 / 66\n", "T0 = 1212\n", @@ -2610,33 +2835,7 @@ "\n", "twin = plt.gca().twinx()\n", "twin.plot(cosp.step_times * 60, cosp.step_temperatures, 'o:')\n", - "twin.set_ylim(1120, 1420)\n", - "\n", - "twin.set_xlim(-60, 59*60)" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "id": "5fb855c8", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([1. , 0.87027027, 0.74736842, 0.63076923, 0.556 ,\n", - " 0.52 , 0.556 , 0.63076923, 0.74736842, 0.87027027,\n", - " 1. , 0.9 , 0.83 , 0.77 , 0.83 ,\n", - " 0.9 , 1. ])" - ] - }, - "execution_count": 44, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "cosp.step_qs / cosp.step_qs[0]" + "twin.set_ylim(1120, 1320)" ] } ],