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.

moduleOutput.f90

@@ -175,13 +175,13 @@ module output
       end do
     end subroutine writeOutputMom
 
-    subroutine writeOutputBoundary(t, dt, n, u, Temp, Zinj)
+    subroutine writeOutputBoundary(t, dt, n, u, Temp, Z_Tne, Zinj)
       use constantParameters, only: eV_to_K
       use referenceValues,    only: t_ref, n_ref, u_ref, Temp_ref
 
       integer, intent(in):: t
       real(dp), intent(in):: dt
-      real(dp), intent(in):: n, u, Temp, Zinj
+      real(dp), intent(in):: n, u, Temp, Z_Tne, Zinj
       character(len=6), parameter:: filename = 'bc.csv'
       logical:: res
 
@@ -189,14 +189,14 @@ module output
       if (.not. res) then
         write (*, '(A, A)') 'Writing: ', filename
         open(unit=dataBC_id, file=pathOutput // filename, action='write', position='append')
-        write(dataBC_id, '(A,4(' // formatSep // ',A))') 't (s)', 'n (m^-3)', 'u (m s^-1)', 'T (eV)','Zinj'
+        write(dataBC_id, '(A,5(' // formatSep // ',A))') 't (s)', 'n_i (m^-3)', 'u_i (m s^-1)', 'T_i (eV)', 'Zinj','Z_Tne'
         close(dataBC_id)
 
       end if
 
       open(unit=dataBC_id, file=pathOutput // filename, action='write', position='append')
-      write(dataBC_id, '(' // formatFloat // ',4('// formatSep // ',' // formatFloat // '))') &
+      write(dataBC_id, '(' // formatFloat // ',5('// formatSep // ',' // formatFloat // '))') &
-                        t*dt*t_ref,  n*n_ref, u*u_ref, Temp*Temp_ref/eV_to_K, Zinj
+                        t*dt*t_ref,  n*n_ref, u*u_ref, Temp*Temp_ref/eV_to_K, Zinj, Z_Tne
 
       close(dataBC_id)
 

scripts_python/plotBC.py

@@ -4,15 +4,17 @@ import numpy as np
 import readBC
 
 
-paths = ['../polytropic_80ns_T30/']
+paths = ['../2025-04-10_08.40.09/']
-time, n, u, T, Zinj = readBC.read(paths[0] + 'bc.csv')
+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, n_e / n_e[0], label = f"$n_e$ ($\\times {n_e[0] * 1e-6:.0e} \\; cm^{{-3}})$")
-plt.plot(time, T / T[0], label = f"$T  \\; (\\times{T[0]:.1f} \\; eV)$")
+plt.plot(time, T_i / T_i[0], label = f"$T  \\; (\\times{T_i[0]:.1f} \\; eV)$")
-plt.plot(time, Zinj, label = "Injection species")
+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
+    start = 80
-    end   = 20#len(filesPhi)
+    end   = 85#len(filesPhi)
-    every = 5
+    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()
+    n = df['n_i (m^-3)'].to_numpy()
-    u = df['u (m s^-1)'].to_numpy()
+    u = df['u_i (m s^-1)'].to_numpy()
-    T = df['T (eV)'].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
 
 

vlaplex.f90

@@ -166,7 +166,7 @@ program VlaPlEx
   write(*, '(A,ES0.4e3)') 'CFL: ', dt*vf/dr
 
   nzMin = 3
-  nzMax = 14
+  nzMax = 13
   nz    = nzMax - nzMin + 1
   nz    = nz + 1 ! Add bin for low Z plasma
   ! Allocate vectors
@@ -189,7 +189,7 @@ program VlaPlEx
   n_e     = 0.0_dp
   T_e     = 0.0_dp
   Zave    = 0.0_dp
-  Z_list(1) = 1.0_dp ! Low Z bin
+  Z_list(1) = 0.1_dp ! Low Z bin
   do iz = nzMin, nzMax
     Z_list(iz-nzMin+1+1) = float(iz)
   end do
@@ -255,23 +255,17 @@ program VlaPlEx
   do t = 1, nt
     time = t * dt + t0
 
-    ! Find new \bar{Z}_i based on T and density
+    ! Get boundary conditions for specific time
     call boundaryConditions%get(time, n_bc, u_bc, Temp_bc)
-    ! Reset previous value
+    ! Find new \bar{Z}_i based on T_e = Temp_bc and n_e = n_bc
-    Zave_bc_old = 0.0_dp
+    call TtoZne%get(Temp_bc, n_bc, Zave_bc)
-    ! Initial guess based on average table
+    ! Assign Z(T,n) to bin
-    call TtoZ%get(Temp_bc, Zave_bc)
     z_inj = minloc(abs(Z_list - Zave_bc),1)
-    Zave_bc     = Z_list(z_inj)
+    ! Calculate inject (sonic) speed
-    ! Start iterative process based on T, n_e table
+    u_bc = sqrt(Z_list(z_inj)* Temp_bc)
-    do while (Zave_bc - Zave_bc_old > 0.1_dp)
+    ! Calculate ion density to inject
-      Zave_bc_old = Zave_bc
+    n_bc = n_bc / Z_list(z_inj)
-      call TtoZne%get(Temp_bc, Zave_bc * n_bc, Zave_bc)
+    call writeOutputBoundary(t, dt, n_bc, u_bc, Temp_bc, Zave_bc, Z_list(z_inj))
-    end do
-    z_inj = minloc(abs(Z_list - Zave_bc),1)
-    Zave_bc     = Z_list(z_inj)
-    u_bc = sqrt(Zave_bc * Temp_bc)
-    call writeOutputBoundary(t, dt, n_bc, u_bc, Temp_bc, Zave_bc)
 
     ! f0(j0:nv) = v(j0:nv)**2 / sqrt(PI*Temp_bc**3) * exp(-(v(j0:nv) - u_bc)**2 / Temp_bc)
     f0(j0:nv) = 1.0_dp / sqrt(PI*Temp_bc) * exp(-(v(j0:nv) - u_bc)**2 / Temp_bc)