varialble Dm balance terms

binning_balance_terms_from_raw.py

@@ -129,6 +129,17 @@ class ConditionalMeanBinning:
         np.savez(self.name, **self.average())
         print("saved ", self.name)
 
+def sutherland(c, dm0=0.02*4./3., rvis=5., pre=2.10e4, ac=26.7, bc=3.):
+    t0 = 1
+    t1 = 1 + bc
+
+    Ts = (rvis * t1 - (t1**(3. / 2.))) / (t1**(3. / 2.) - rvis)
+    As = t0 + Ts
+
+    theta = (1 + bc * c)
+
+    return dm0 * As * np.sqrt(theta) / (1. + Ts / theta)
+
 
 cs = CompactScheme(nx, ny, nz, False, True, True, 4, 2, 2)
 
@@ -136,6 +147,10 @@ cs = CompactScheme(nx, ny, nz, False, True, True, 4, 2, 2)
 cmean_verify = np.zeros(len(x_indices))
 
 # Conditional Average Objects
+avg_objs_ddxdmddxc = [ConditionalMeanBinning(var='ddxdmddxc', case=casename, loc=xi) for xi in x_indices]
+avg_objs_ddydmddyc = [ConditionalMeanBinning(var='ddydmddyc', case=casename, loc=xi) for xi in x_indices]
+avg_objs_ddzdmddzc = [ConditionalMeanBinning(var='ddzdmddzc', case=casename, loc=xi) for xi in x_indices]
+
 avg_objs_ddxc = [ConditionalMeanBinning(var='ddxc', case=casename, loc=xi) for xi in x_indices]
 avg_objs_ddyc = [ConditionalMeanBinning(var='ddyc', case=casename, loc=xi) for xi in x_indices]
 avg_objs_ddzc = [ConditionalMeanBinning(var='ddzc', case=casename, loc=xi) for xi in x_indices]
@@ -147,8 +162,6 @@ avg_objs_uddxc = [ConditionalMeanBinning(var='uddxc', case=casename, loc=xi) for
 avg_objs_vddyc = [ConditionalMeanBinning(var='vddyc', case=casename, loc=xi) for xi in x_indices]
 avg_objs_wddzc = [ConditionalMeanBinning(var='wddzc', case=casename, loc=xi) for xi in x_indices]
 
-avg_objs_ddxcddxc = [ConditionalMeanBinning(var='ddxcddxc', case=casename, loc=xi) for xi in x_indices]
-
 targets=[ 'ddxc', 'ddyc', 'ddzc', 'd2dxc', 'd2dyc', 'd2dzc', 'uddxc', 'vddyc', 'wddzc', ]
 mean_array = np.zeros((10, nx))
 
@@ -162,27 +175,38 @@ for i, fname in enumerate(case.data_files[:n_timestep]):
     u = u+u0
     y = scalar[-1]
     c = (1. - y)
+    dm = sutherland(c)
 
     d2dxc = cs.d2dx(c)
     d2dyc = cs.d2dy(c)
     d2dzc = cs.d2dz(c)
 
+    ddxdm = cs.ddx(dm)
+    ddydm = cs.ddy(dm)
+    ddzdm = cs.ddz(dm)
+
     ddzc = cs.ddz(c)
     ddyc = cs.ddy(c)
     ddxc = cs.ddx(c)
 
-    ddxcddxc = ddxc * ddxc
-
     uddxc = u*ddxc
     vddyc = v*ddyc
     wddzc = w*ddzc
 
+    ddxdmddxc = ddxdm*ddxc
+    ddydmddyc = ddydm*ddyc
+    ddzdmddzc = ddzdm*ddzc
+
     for idx, field in enumerate([u, v, w, c, ddxc, ddyc, ddzc, d2dxc, d2dyc, d2dzc]):
         mean_array[idx] += field.sum(axis=(0,1))
 
     for j, xi in enumerate(x_indices):
         mask = avg_objs_ddxc[j].calculate_conditional_mask(c[:,:,xi])
 
+        avg_objs_ddxdmddxc[j].feed_samples(c[:,:,xi], ddxdmddxc[:,:,xi], mask)
+        avg_objs_ddydmddyc[j].feed_samples(c[:,:,xi], ddydmddyc[:,:,xi], mask)
+        avg_objs_ddzdmddzc[j].feed_samples(c[:,:,xi], ddzdmddzc[:,:,xi], mask)
+
         avg_objs_ddxc[j].feed_samples(c[:,:,xi], ddxc[:,:,xi], mask)
         avg_objs_ddyc[j].feed_samples(c[:,:,xi], ddyc[:,:,xi], mask)
         avg_objs_ddzc[j].feed_samples(c[:,:,xi], ddzc[:,:,xi], mask)
@@ -191,8 +215,6 @@ for i, fname in enumerate(case.data_files[:n_timestep]):
         avg_objs_d2dyc[j].feed_samples(c[:,:,xi], d2dyc[:,:,xi], mask)
         avg_objs_d2dzc[j].feed_samples(c[:,:,xi], d2dzc[:,:,xi], mask)
 
-        avg_objs_ddxcddxc[j].feed_samples(c[:,:,xi], ddxcddxc[:,:,xi], mask)
-
         avg_objs_uddxc[j].feed_samples(c[:,:,xi], uddxc[:,:,xi], mask)
         avg_objs_vddyc[j].feed_samples(c[:,:,xi], vddyc[:,:,xi], mask)
         avg_objs_wddzc[j].feed_samples(c[:,:,xi], wddzc[:,:,xi], mask)
@@ -216,6 +238,10 @@ def save_cmean_result (fmt, obj_list):
     for j, xi in enumerate(x_indices):
         obj_list[j].save_to_file()
 
+save_cmean_result("cavg_ddxdmddxc_c_{}_{}", avg_objs_ddxdmddxc)
+save_cmean_result("cavg_ddydmddyc_c_{}_{}", avg_objs_ddydmddyc)
+save_cmean_result("cavg_ddzdmddzc_c_{}_{}", avg_objs_ddzdmddzc)
+
 save_cmean_result("cavg_ddxc_c_{}_{}", avg_objs_ddxc)
 save_cmean_result("cavg_ddyc_c_{}_{}", avg_objs_ddyc)
 save_cmean_result("cavg_ddzc_c_{}_{}", avg_objs_ddzc)
@@ -227,5 +253,3 @@ save_cmean_result("cavg_wddzc_c_{}_{}", avg_objs_wddzc)
 save_cmean_result("cavg_d2dxc_c_{}_{}", avg_objs_d2dxc)
 save_cmean_result("cavg_d2dyc_c_{}_{}", avg_objs_d2dyc)
 save_cmean_result("cavg_d2dzc_c_{}_{}", avg_objs_d2dzc)
-
-save_cmean_result("cavg_ddxcddxc_c_{}_{}", avg_objs_ddxcddxc)