Loading a MAST-U plasma from SOLPS¶

Example of how to load a plasma from an existing SOLPS simulation (demo file). Also, shows how to inspect the plasma parameters. Start by importing all required modules.

import matplotlib.pyplot as plt
import numpy as np
from cherab.core.atomic.elements import carbon, deuterium
from cherab.solps import SOLPSSimulation
plt.ion()

Import the SOLPS simulation from AUG MDSplus server.

mds_server = 'solps-mdsplus.aug.ipp.mpg.de:8001'
ref_number = 69636

sim = SOLPSSimulation.load_from_mdsplus(mds_server, ref_number)
plasma = sim.plasma
mesh = sim.mesh
vessel = mesh.vessel

The plasma parameters are loaded automatically from the simulation. We can now access an individual species using the get_species method. It takes as argument the element/isotope of interest and the desired charge state. If the species requested was not in the simulation, an exception will be thrown.

d0 = plasma.composition.get(deuterium, 0)
d1 = plasma.composition.get(deuterium, 1)
c0 = plasma.composition.get(carbon, 0)
c1 = plasma.composition.get(carbon, 1)
c2 = plasma.composition.get(carbon, 2)
c3 = plasma.composition.get(carbon, 3)
c4 = plasma.composition.get(carbon, 4)
c5 = plasma.composition.get(carbon, 5)
c6 = plasma.composition.get(carbon, 6)

The electron distribution is the only exception to the above access pattern. It is accessed with a dedicated plasma attribute, plasma.electron_distribution.

Now we will sample the different species values over a regular grid in the poloidal plane. Results for density, temperature and velocity are plotted, along with the SOLPS simulation grid.

xl, xu = (0.0, 2.0)
yl, yu = (-2.0, 2.0)
te_samples = np.zeros((500, 500))
ne_samples = np.zeros((500, 500))
d0_samples = np.zeros((500, 500))
d1_samples = np.zeros((500, 500))
c0_samples = np.zeros((500, 500))
c1_samples = np.zeros((500, 500))
c2_samples = np.zeros((500, 500))
c3_samples = np.zeros((500, 500))
c4_samples = np.zeros((500, 500))
c5_samples = np.zeros((500, 500))
c6_samples = np.zeros((500, 500))
d0_velocity = np.zeros((500, 500))
d1_velocity = np.zeros((500, 500))
xrange = np.linspace(xl, xu, 500)
yrange = np.linspace(yl, yu, 500)


for i, x in enumerate(xrange):
    for j, y in enumerate(yrange):
        ne_samples[j, i] = plasma.electron_distribution.density(x, 0.0, y)
        te_samples[j, i] = plasma.electron_distribution.effective_temperature(x, 0.0, y)
        d0_samples[j, i] = d0.distribution.density(x, 0.0, y)
        d1_samples[j, i] = d1.distribution.density(x, 0.0, y)
        c0_samples[j, i] = c0.distribution.density(x, 0.0, y)
        c1_samples[j, i] = c1.distribution.density(x, 0.0, y)
        c2_samples[j, i] = c2.distribution.density(x, 0.0, y)
        c3_samples[j, i] = c3.distribution.density(x, 0.0, y)
        c4_samples[j, i] = c4.distribution.density(x, 0.0, y)
        c5_samples[j, i] = c5.distribution.density(x, 0.0, y)
        c6_samples[j, i] = c6.distribution.density(x, 0.0, y)
        # magnitude of velocity vector
        d0_velocity[j, i] = d0.distribution.bulk_velocity(x, 0.0, y).length
        d1_velocity[j, i] = d1.distribution.bulk_velocity(x, 0.0, y).length

# Turn on interactive plotting.
plt.ion()

mesh.plot_mesh()
plt.title('mesh geometry')

plt.figure()
plt.imshow(ne_samples, extent=[xl, xu, yl, yu], origin='lower')
plt.colorbar()
plt.xlim(xl, xu)
plt.ylim(yl, yu)
plt.title("electron density")
plt.figure()
plt.imshow(te_samples, extent=[xl, xu, yl, yu], origin='lower')
plt.colorbar()
plt.xlim(xl, xu)
plt.ylim(yl, yu)
plt.title("electron temperature")

plt.figure()
plt.imshow(d0_samples, extent=[xl, xu, yl, yu], origin='lower')
plt.colorbar()
plt.xlim(xl, xu)
plt.ylim(yl, yu)
plt.title("D0 density")
plt.figure()
plt.imshow(d1_samples, extent=[xl, xu, yl, yu], origin='lower')
plt.colorbar()
plt.xlim(xl, xu)
plt.ylim(yl, yu)
plt.title("DI density")

plt.figure()
plt.imshow(c0_samples, extent=[xl, xu, yl, yu], origin='lower')
plt.colorbar()
plt.xlim(xl, xu)
plt.ylim(yl, yu)
plt.title("CI density")
plt.figure()
plt.imshow(c1_samples, extent=[xl, xu, yl, yu], origin='lower')
plt.colorbar()
plt.xlim(xl, xu)
plt.ylim(yl, yu)
plt.title("CII density")
plt.figure()
plt.imshow(c2_samples, extent=[xl, xu, yl, yu], origin='lower')
plt.colorbar()
plt.xlim(xl, xu)
plt.ylim(yl, yu)
plt.title("CIII density")
plt.figure()
plt.imshow(c3_samples, extent=[xl, xu, yl, yu], origin='lower')
plt.colorbar()
plt.xlim(xl, xu)
plt.ylim(yl, yu)
plt.title("CIV density")
plt.figure()
plt.imshow(c4_samples, extent=[xl, xu, yl, yu], origin='lower')
plt.colorbar()
plt.xlim(xl, xu)
plt.ylim(yl, yu)
plt.title("CV density")
plt.figure()
plt.imshow(c5_samples, extent=[xl, xu, yl, yu], origin='lower')
plt.colorbar()
plt.xlim(xl, xu)
plt.ylim(yl, yu)
plt.title("CVI density")
plt.figure()
plt.imshow(c6_samples, extent=[xl, xu, yl, yu], origin='lower')
plt.colorbar()
plt.xlim(xl, xu)
plt.ylim(yl, yu)
plt.title("CVII density")

plt.figure()
plt.imshow(d0_velocity, extent=[xl, xu, yl, yu], origin='lower')
plt.colorbar()
plt.xlim(xl, xu)
plt.ylim(yl, yu)
plt.title("D0 velocity")

plt.figure()
plt.imshow(d1_velocity, extent=[xl, xu, yl, yu], origin='lower')
plt.colorbar()
plt.xlim(xl, xu)
plt.ylim(yl, yu)
plt.title("D1 velocity")