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Smaller grid size and BC to ensure reaching a quasi-steady state after 80 ns in the domain

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Jorge Gonzalez 2024-11-28 10:57:27 +01:00
commit db7077efc0
4 changed files with 24 additions and 24 deletions
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21
scripts_python/plotCumF.py
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@ -11,27 +11,28 @@ m_i = 1.9712e-25
# paths = ['../quasiNeutral_partialAblation/','../Poisson_partialAblation/','../PoissonTi_partialAblation/','../2024-11-05_13.56.23/']
# paths = ['../2024-11-11_13.58.54/']
# paths = ['../quasiNeutral_fullAblation/','../Poisson_fullAblation/', '../quasiNeutral_partialAblation/', '../Poisson_partialAblation/']
paths = ['../2024-11-18_11.54.30/']
paths = ['../2024-11-28_10.01.56/']
# paths = ['../Poisson_partialAblation/','../Poisson_partialAblation_lowerT/','../Poisson_partialAblation_lowT/','../Poisson_partialAblation_highT/']
labels = [path[3:-1] for path in paths]
for path, label in zip(paths, labels):
filesCum_i = sorted(glob.glob(path+'time_*_fCum_i.csv'))
start = 0
end = len(filesCum_i)
every = 50
every = 20
for fileCum_i in filesCum_i[start:end+1:every]:
time, x, v, f_i = readF.read(fileCum_i)
plt.plot(v**2*m_i*0.5/e, f_i[0]*e/m_i/v, label='t = {:.1f} ns'.format(time*1e9))
# time, x, v, f_i = readF.read(filesCum_i[-1])
# plt.plot(v**2*m_i*0.5/e, f_i[0]*e/m_i/v, label=label)
time, x, v, f_i = readF.read(filesCum_i[-1])
plt.plot(v**2*m_i*0.5/e, f_i[0]*e/m_i/v, label=label)
plt.yscale('log')
plt.ylim([1e16,5e27])
plt.ylabel('Sum f(e) / sqrt(e) (m^-3 eV^-1)')
plt.xscale('log')
plt.xlim([1e0,1e4])
plt.xlabel('e (eV)')
plt.yscale('log')
plt.ylim([1e16,5e27])
plt.ylabel('Sum f(e) / sqrt(e) (m^-3 eV^-1)')
plt.xscale('log')
plt.xlim([1e0,1e4])
plt.xlabel('e (eV)')
plt.legend()

14
scripts_python/plotMom.py
View file

@ -11,25 +11,25 @@ from scipy.constants import e, k
# paths = ['../quasiNeutral_partialAblation/','../Poisson_partialAblation/']
# paths = ['../2024-10-02_14.30.44/']
# paths = ['../quasiNeutral_fullAblation/','../Poisson_fullAblation/']
paths = ['../2024-11-18_08.57.04/']
paths = ['../2024-11-28_10.01.56/']
labels = [path[3:-1] for path in paths]
for path, label in zip(paths, labels):
filesPhi = sorted(glob.glob(path+'time_*_phi.csv'))
filesMom_i = sorted(glob.glob(path+'time_*_mom_i.csv'))
start = 500
end = len(filesMom_i)
every = 200
start = 0
end = 50#len(filesMom_i)
every = 10
fig, ax = plt.subplots(4, sharex='all')
for fileMom_i, filePhi in zip(filesMom_i[start:end+1:every], filesPhi[start:end+1:every]):
time, r, phi, E, n_e = readPhi.read(filePhi)
time, r, n_i, u_i, T_i, Zave = readMom.read(fileMom_i)
# ax[0].plot(r, phi, label='t = {:.1f} ns'.format(time*1e9))
ax[0].plot(r, E, label='t = {:.1f} ns'.format(time*1e9))
# ax[0].plot(r, (Zave*n_i - n_e)/n_e, label='t = {:.1f} ns'.format(time*1e9))
# ax[0].plot(r, E, label='t = {:.1f} ns'.format(time*1e9))
ax[0].plot(r, (Zave*n_i - n_e), label='t = {:.1f} ns'.format(time*1e9))
ax[1].set_yscale('log')
ax[1].set_ylim([1e20,2e25])
# ax[1].set_ylim(bottom=1e16)
ax[1].plot(r, Zave*n_i)
ax[1].plot(r, n_e, color='k', linestyle='dashed')
ax[2].plot(r, u_i)