epsR = pR / rhoR / (gamma - 1)
qL = numpy.array([rhoL, 0, vyL, vzL, epsL, Bx, ByL, BzL, 0, 0, 0, 0, 0])
qR = numpy.array([rhoR, 0, vyR, vzR, epsR, Bx, ByR, BzR, 0, 0, 0, 0, 0])
sigma_s = [0, 10, 10**2, 10**3, 10**6] # Can even do 10^9 now
Bys = []
for sigma in sigma_s:
model = sr_rmhd.sr_rmhd_gamma_law(initial_data=sr_rmhd.initial_riemann(
qL, qR),
gamma=gamma,
sigma=sigma)
fast_source = model.relaxation_source()
sim = simulation(model,
interval,
fvs_method(2),
imex222(fast_source),
outflow,
cfl=0.25)
sim.evolve(0.4)
print("sigma={}".format(sigma))
sim.plot_system()
pyplot.show()
Bys.append(sim.cons[6, :].copy())
fig = pyplot.figure()
ax = fig.add_subplot(111)
ax.set_prop_cycle=cycler('color', ['red','green','blue','yellow','cyan']) + \
cycler('linestyle', ['-', '--', '-.', ':', '--'])
for sigma, By in zip(sigma_s, Bys):
ax.plot(sim.coordinates, By, label=r"$\sigma={}$".format(sigma))
ax.set_xlabel(r"$x$")
Ngz = 3 Npoints = 800 L = 0.5 interval = grid([-L, L], Npoints, Ngz) rhoL = 1 pL = 5 rhoR = 0.9 pR = 5.3 vyL = 0.3 vyR = 0 vzL = 0.4 vzR = 0 Bx = 1 ByL = 6 ByR = 5 BzL = 2 BzR = 2 gamma = 5/3 epsL = pL / rhoL / (gamma - 1) epsR = pR / rhoR / (gamma - 1) qL = numpy.array([rhoL, 0, vyL, vzL, epsL, Bx , ByL , BzL ]) qR = numpy.array([rhoR, 0, vyR, vzR, epsR, Bx , ByR , BzR ]) model = sr_mhd.sr_mhd_gamma_law(initial_data = sr_mhd.initial_riemann(qL, qR), gamma=gamma) sim = simulation(model, interval, fvs_method(2), rk3, outflow, cfl=0.5) sim.evolve(0.4) sim.plot_system() pyplot.show()
Ngz = 4
Npoints = 100
tau = 1
L = 10
interval = grid([0, L], Npoints, Ngz)
# Initial data. (Mis)use RP for trivial constant data
rho_init = 34.37746770
v_init = 18
p_init = 1589.2685472 # Not actually used, but in the paper
T_init = 43.0351225511 # Hand calculation, works only for default values
eps_init = T_init / (5 / 3 - 1)
E_init = rho_init * (v_init**2 / 2 + eps_init)
qL = numpy.array([rho_init, v_init, eps_init])
qR = numpy.array([rho_init, v_init, eps_init])
model = euler_relaxation.euler_relaxation(
initial_data=euler_relaxation.initial_riemann(qL, qR))
slow_source = model.source()
fast_source = model.relaxation_source(tau)
sim = simulation(model,
interval,
fvs_method(2, slow_source),
imex222(fast_source),
outflow_reflect_right,
cfl=0.25)
sim.evolve(0.035)
sim.plot_system()
pyplot.show()