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# Copyright 2024 DeepMind Technologies Limited | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
"""Base class and utils for TGLF-based models.""" | ||
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import chex | ||
from jax import numpy as jnp | ||
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from torax import geometry | ||
from torax import physics | ||
from torax import state | ||
from torax.constants import CONSTANTS | ||
from torax.transport_model import quasilinear_transport_model | ||
from torax.transport_model import runtime_params as runtime_params_lib | ||
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@chex.dataclass | ||
class RuntimeParams(quasilinear_transport_model.RuntimeParams): | ||
pass | ||
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@chex.dataclass(frozen=True) | ||
class DynamicRuntimeParams(quasilinear_transport_model.DynamicRuntimeParams): | ||
pass | ||
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@chex.dataclass | ||
class RuntimeParamsProvider(runtime_params_lib.RuntimeParamsProvider): | ||
pass | ||
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@chex.dataclass(frozen=True) | ||
class TGLFInputs(quasilinear_transport_model.QuasilinearInputs): | ||
r"""Dimensionless inputs to the TGLF model. | ||
See https://gafusion.github.io/doc/tglf/tglf_table.html for definitions. | ||
""" | ||
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# Ti/Te | ||
Ti_over_Te: chex.Array | ||
# dRmaj/dr | ||
dRmaj: chex.Array | ||
# q | ||
q: chex.Array | ||
# r/q dq/dr | ||
s_hat: chex.Array | ||
# nu_ei (see note in prepare_tglf_inputs) | ||
ei_collision_freq: chex.Array | ||
# Elongation kappa | ||
kappa: chex.Array | ||
# r/kappa dkappa/dr | ||
kappa_shear: chex.Array | ||
# Triangularity delta | ||
delta: chex.Array | ||
# r ddelta/dr | ||
delta_shear: chex.Array | ||
# Electron pressure defined w.r.t B_unit | ||
beta_e: chex.Array | ||
# Effective charge | ||
Zeff: chex.Array | ||
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class TGLFBasedTransportModel(quasilinear_transport_model.QuasilinearTransportModel): | ||
"""Base class for TGLF-based transport models.""" | ||
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def _prepare_tglf_inputs( | ||
Zeff_face: chex.Array, | ||
nref: chex.Numeric, | ||
q_correction_factor: chex.Numeric, | ||
transport: DynamicRuntimeParams, | ||
geo: geometry.Geometry, | ||
core_profiles: state.CoreProfiles, | ||
) -> TGLFInputs: | ||
# Shorthand for the appropriate variables | ||
Te = core_profiles.temp_el | ||
Ti = core_profiles.temp_ion | ||
ne = core_profiles.ne | ||
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# Reference velocity and length, used for normalisation | ||
vref = (Te.face_value() / (core_profiles.Ai * CONSTANTS.mp)) ** 0.5 | ||
lref = geo.Rmin[-1] # Minor radius at LCFS | ||
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# Temperature gradients | ||
Ti_over_Te = Ti.face_value() / Te.face_value() | ||
Ate = -lref / Te.face_value() * Te.face_grad() | ||
Ati = -lref / Ti.face_value() * Ti.face_grad() | ||
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# Density gradient | ||
# Note: nref cancels, as 1/(ne*nref) * (ne_grad * nref) = 1/ne * ne_grad | ||
Ane = -lref / ne.face_value() * core_profiles.ne.face_grad() | ||
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# Electron-electron collision frequency | ||
# Note: In the TGLF docs, XNUE is mislabelled. | ||
# It is actually the electron-electron collision frequency | ||
# See https://pyrokinetics.readthedocs.io/en/latest/user_guide/collisions.html | ||
Lambda_ee = physics._calculate_lambda_ee(Te, ne) | ||
normalised_nu_ee = (4 * jnp.pi * ne * CONSTANTS.qe**4 * Lambda_ee) / ( | ||
CONSTANTS.me**0.5 * (2 * Te) ** 1.5 | ||
) | ||
nu_ee = normalised_nu_ee / (vref / lref) | ||
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# Safety factor | ||
# Need to recalculate since in the nonlinear solver psi has intermediate | ||
# states in the iterative solve | ||
q, _ = physics.calc_q_from_psi( | ||
geo=geo, | ||
psi=core_profiles.psi, | ||
q_correction_factor=q_correction_factor, | ||
) | ||
# Shear uses rho_face_norm | ||
# TODO: check whether this should be midplane R | ||
s_hat = physics.calc_s_from_psi(geo, core_profiles.psi) # = r/q dq/dr | ||
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# Electron beta | ||
p_e = ne * (Te * 1e3) # ne in m^-3, Te in eV | ||
# B_unit = q/r dpsi/dr | ||
B_unit = ( | ||
q / geo.rho_face_norm * jnp.gradient(core_profiles.psi, geo.rho_face_norm) | ||
) | ||
beta_e = 8 * jnp.pi * p_e / B_unit**2 | ||
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# Geometry | ||
Rmaj = geo.Rmaj | ||
Rmin = geo.Rmin | ||
dRmaj = jnp.gradient(geo.Rmaj, geo.rho_face_norm) | ||
kappa = geo.elongation_face | ||
# Elongation | ||
kappa_shear = geo.rho_face_norm / kappa * jnp.gradient(kappa, geo.rho_face_norm) | ||
# Triangularity | ||
delta = geo.delta_face | ||
delta_shear = geo.delta_face * jnp.gradient(geo.delta_face, geo.rho_face_norm) | ||
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# Gyrobohm diffusivity | ||
# Used to unnormalise the outputs | ||
# TODO: check this definition with Lorenzo/TGLF and ensure correct normalisation | ||
chiGB = ( | ||
(core_profiles.Ai * CONSTANTS.mp) ** 0.5 | ||
/ (CONSTANTS.qe * geo.B0) ** 2 | ||
* (Ti.face_value() * CONSTANTS.keV2J) ** 1.5 | ||
/ lref | ||
) | ||
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return TGLFInputs( | ||
# From QuasilinearInputs | ||
chiGB=chiGB, | ||
Rmin=Rmin, | ||
Rmaj=Rmaj, | ||
Ati=Ati, | ||
Ate=Ate, | ||
Ane=Ane, | ||
# From TGLFInputs | ||
Ti_over_Te=Ti_over_Te, | ||
dRmaj=dRmaj, | ||
q=q, | ||
s_hat=s_hat, | ||
nu_ee=nu_ee, | ||
kappa=kappa, | ||
kappa_shear=kappa_shear, | ||
delta=delta, | ||
delta_shear=delta_shear, | ||
beta_e=beta_e, | ||
Zeff=Zeff_face, | ||
) |
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