n_e as boundary condition

Now n_e is given as the density at the boundary and n_i at the boundary
is calculated once Z is known.

This aims to eliminate the iterative process.

scripts_python/plotBC.py

@@ -4,15 +4,17 @@ import numpy as np
 import readBC
 
 
-paths = ['../polytropic_80ns_T30/']
-time, n, u, T, Zinj = readBC.read(paths[0] + 'bc.csv')
+paths = ['../2025-04-10_08.40.09/']
+time, n_i, u_i, T_i, Zinj, Z_Tne = readBC.read(paths[0] + 'bc.csv')
 
 fig, ax = plt.subplots()
 
+n_e = n_i * Zinj
 
-plt.plot(time, n / n[0], label = f"$n_i$ ($\\times {n[0] * 1e-6:.0e} \\; cm^{{-3}})$")
-plt.plot(time, T / T[0], label = f"$T  \\; (\\times{T[0]:.1f} \\; eV)$")
-plt.plot(time, Zinj, label = "Injection species")
+plt.plot(time, n_e / n_e[0], label = f"$n_e$ ($\\times {n_e[0] * 1e-6:.0e} \\; cm^{{-3}})$")
+plt.plot(time, T_i / T_i[0], label = f"$T  \\; (\\times{T_i[0]:.1f} \\; eV)$")
+plt.plot(time, Zinj, label = "Zinj")
+plt.plot(time, Z_Tne, label = "Z_Tne")
 plt.semilogy()
 plt.legend()
 plt.show()

scripts_python/plotCumF.py

@@ -16,7 +16,7 @@ m_i = 1.9712e-25
 #  paths = ['../2024-12-10_18.45.17/', '../Poisson_50ns_T30Z11/']
 #  paths = ['../2024-12-11_12.38.27/', '../Poisson_polytropic_fa_T30Z11/', '../Poisson_fa_T30Z11/']
 #  paths = ['../Poisson_partialAblation/','../Poisson_partialAblation_lowerT/','../Poisson_partialAblation_lowT/','../Poisson_partialAblation_highT/']
-paths = ['../polytropic_80ns_T60/']
+paths = ['../polytropic_80ns_T30/']
 labels = [path[3:-1] for path in paths]
 
 for path, label in zip(paths, labels):
@@ -26,10 +26,12 @@ for path, label in zip(paths, labels):
     sumF = np.zeros(len(v))
 
     for Z in Zlist:
-        filesCum_i = sorted(glob.glob(path+'time_*_Z{:.0f}000_fCum_i.csv'.format(Z)))
+        filename='time_*_Z_{:.1f}_fCum_i.csv'.format(Z)
+        filesCum_i = sorted(glob.glob(path+filename))
         time, x, v, f_i = readF.read(filesCum_i[-1])
         sumF += f_i[0]
         plt.plot(v**2*m_i*0.5/e, f_i[0]*e/m_i/v, label=Z)
+    print(time)
     plt.plot(v**2*m_i*0.5/e, sumF*e/m_i/v, label='sum', color='k', linestyle='dashed')
 
 plt.yscale('log')

scripts_python/plotMom.py

@@ -12,15 +12,15 @@ from scipy.constants import e, k
 #  paths = ['../quasiNeutral_partialAblation/','../Poisson_partialAblation/']
 #  paths = ['../2024-10-02_14.30.44/']
 #  paths = ['../quasiNeutral_fullAblation/','../Poisson_fullAblation/']
-paths = ['../2025-04-08_09.36.52/']
+paths = ['../2025-04-09_16.45.52/']
 labels = [path[3:-1] for path in paths]
 
 for path, label in zip(paths, labels):
     Zlist      = readZlist.read(path+'ZList.csv')
     filesPhi   = sorted(glob.glob(path+'time_*_phi.csv'))
-    start = 0
-    end   = 20#len(filesPhi)
-    every = 5
+    start = 80
+    end   = 85#len(filesPhi)
+    every = 1
     fig, ax = plt.subplots(4, sharex='all')
     ax[1].set_yscale('log')
     ax[1].set_ylim(bottom=1e10, top=1e24)
@@ -30,7 +30,8 @@ for path, label in zip(paths, labels):
         ave_ui  = np.zeros(len(r))
         ave_Ti  = np.zeros(len(r))
         for Z in Zlist:
-            filesMom_i = sorted(glob.glob(path+'time_*_Z{:.0f}000_mom_i.csv'.format(Z)))
+            filename='time_*_Z_{:.1f}_mom_i.csv'.format(Z)
+            filesMom_i = sorted(glob.glob(path+filename))
             fileMom_i = filesMom_i[t]
             time, r, n_i, u_i, T_i, Zave = readMom.read(fileMom_i)
             sum_Zni += Zave*n_i

scripts_python/readBC.py

@@ -4,11 +4,12 @@ def read(filename):
     # Get time
     df = pandas.read_csv(filename)
     time = df['t (s)'].to_numpy()
-    n = df['n (m^-3)'].to_numpy()
-    u = df['u (m s^-1)'].to_numpy()
-    T = df['T (eV)'].to_numpy()
+    n = df['n_i (m^-3)'].to_numpy()
+    u = df['u_i (m s^-1)'].to_numpy()
+    T = df['T_i (eV)'].to_numpy()
     Zinj = df['Zinj'].to_numpy()
+    Z_Tne = df['Z_Tne'].to_numpy()
 
-    return time, n, u, T, Zinj
+    return time, n, u, T, Zinj, Z_Tne