diff --git a/pyproject.toml b/pyproject.toml index 027c3839..8b9730db 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -34,6 +34,8 @@ dependencies = [ "h5netcdf>=1.3.0", "scipy>=1.12.0", "jaxtyping>=0.2.28", + "contourpy>=1.2.1", + "eqdsk>=0.4.0" ] [project.urls] diff --git a/torax/config/build_sim.py b/torax/config/build_sim.py index 602778ad..a997da43 100644 --- a/torax/config/build_sim.py +++ b/torax/config/build_sim.py @@ -54,6 +54,8 @@ def _build_standard_geometry_provider( intermediate_builder = geometry.StandardGeometryIntermediates.from_chease elif geometry_type == 'fbt': intermediate_builder = geometry.StandardGeometryIntermediates.from_fbt + elif geometry_type == 'eqdsk': + intermediate_builder = geometry.StandardGeometryIntermediates.from_eqdsk else: raise ValueError(f'Unknown geometry type: {geometry_type}') if 'geometry_configs' in kwargs: @@ -143,10 +145,12 @@ def build_geometry_provider_from_config( geometry_type = kwargs.pop('geometry_type').lower() # Remove from kwargs. if geometry_type == 'circular': return _build_circular_geometry_provider(**kwargs) - elif geometry_type == 'chease' or geometry_type == 'fbt': + # elif geometry_type == 'chease' or geometry_type == 'fbt': + elif geometry_type in ['chease', 'fbt', 'eqdsk']: return _build_standard_geometry_provider( geometry_type=geometry_type, **kwargs ) + raise ValueError(f'Unknown geometry type: {geometry_type}') diff --git a/torax/data/third_party/geo/eqdsk_cocos02.eqdsk b/torax/data/third_party/geo/eqdsk_cocos02.eqdsk new file mode 100644 index 00000000..3562e761 --- /dev/null +++ b/torax/data/third_party/geo/eqdsk_cocos02.eqdsk @@ -0,0 +1,3722 @@ +Tokamak name.M #00000 t= 0.0 29-Aug-2024 3 129 129 + 5.329999328E-01 1.519999981E+00 8.800000000E-01 6.140000224E-01 0.000000000E+00 + 9.025221467E-01 3.618796170E-02-2.609100957E-02 0.000000000E+00 1.436964362E+00 + 1.753041406E+05-2.609100957E-02 0.000000000E+00 9.025221467E-01 0.000000000E+00 + 3.618796170E-02 0.000000000E+00 0.000000000E+00 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00000000..6ed08f4d --- /dev/null +++ b/torax/examples/eqdsk_example.py @@ -0,0 +1,87 @@ +# 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. + +"""ITER hybrid scenario based (roughly) on van Mulders NF 2021.""" + + +CONFIG = { + 'runtime_params': {}, + 'geometry': { + 'geometry_type': 'EQDSK', + 'geometry_file': 'eqdsk_cocos02.eqdsk', + 'Ip_from_parameters': True, + }, + 'sources': { + # Current sources (for psi equation) + 'j_bootstrap': {}, + 'jext': {}, + # Electron density sources/sink (for the ne equation). + 'nbi_particle_source': {}, + 'gas_puff_source': {}, + 'pellet_source': {}, + # Ion and electron heat sources (for the temp-ion and temp-el eqs). + 'generic_ion_el_heat_source': {}, + 'fusion_heat_source': {}, + 'qei_source': {}, + 'ohmic_heat_source': {}, + }, + 'transport': { + 'transport_model': 'qlknn', + # set inner core transport coefficients (ad-hoc MHD/EM transport) + 'apply_inner_patch': True, + 'De_inner': 0.25, + 'Ve_inner': 0.0, + 'chii_inner': 1.0, + 'chie_inner': 1.0, + 'rho_inner': 0.2, # radius below which patch transport is applied + # set outer core transport coefficients (L-mode near edge region) + 'apply_outer_patch': True, + 'De_outer': 0.1, + 'Ve_outer': 0.0, + 'chii_outer': 2.0, + 'chie_outer': 2.0, + 'rho_outer': 0.9, # radius above which patch transport is applied + # allowed chi and diffusivity bounds + 'chimin': 0.05, # minimum chi + 'chimax': 100, # maximum chi (can be helpful for stability) + 'Demin': 0.05, # minimum electron diffusivity + 'qlknn_params': { + 'DVeff': True, + 'coll_mult': 0.25, + 'include_ITG': True, # to toggle ITG modes on or off + 'include_TEM': True, # to toggle TEM modes on or off + 'include_ETG': True, # to toggle ETG modes on or off + # ensure that smag - alpha > -0.2 always, to compensate for no slab + # modes + 'avoid_big_negative_s': True, + # minimum |R/Lne| below which effective V is used instead of + # effective D + 'An_min': 0.05, + 'ITG_flux_ratio_correction': 1, + }, + }, + 'stepper': { + 'stepper_type': 'linear', + 'predictor_corrector': True, + 'corrector_steps': 1, + # (deliberately) large heat conductivity for Pereverzev rule + 'chi_per': 30, + # (deliberately) large particle diffusion for Pereverzev rule + 'd_per': 15, + 'use_pereverzev': True, + }, + 'time_step_calculator': { + 'calculator_type': 'chi', + }, +} diff --git a/torax/geometry.py b/torax/geometry.py index 47d74885..b4fdaa31 100644 --- a/torax/geometry.py +++ b/torax/geometry.py @@ -28,6 +28,7 @@ import jax.numpy as jnp import numpy as np import scipy +from contourpy import contour_generator from torax import constants from torax import geometry_loader from torax import interpolated_param @@ -879,6 +880,197 @@ def from_fbt( hires_fac=hires_fac, ) + @classmethod + def from_eqdsk( + cls, + geometry_dir: str | None = None, + geometry_file: str = 'eqdsk_cocos02.eqdsk', + hires_fac: int = 4, + Ip_from_parameters: bool = True, + n_rho: int = 25, + ): + """NOTE: Different from other geometry loaders, the shaping factors are coming from eqdsk""" + + + def calculate_area(x, z): + """Gauss-shoelace formula (https://en.wikipedia.org/wiki/Shoelace_formula)""" + n = len(x) + area = 0.0 + for i in range(n): + j = (i + 1) % n # roll over at n + area += x[i] * z[j] + area -= z[i] * x[j] + area = abs(area) / 2.0 + return area + + eqfile = geometry_loader.load_geo_data(geometry_dir, geometry_file, geometry_loader.GeometrySource.EQDSK) + + Rmaj = eqfile['xmag'] + Rmin = eqfile['xbdry'].max() - Rmaj + B0 = eqfile['bcentre'] + + psi_eqdsk_1dgrid = np.linspace(eqfile['psimag'], eqfile['psibdry'], eqfile['nx']) + + X_1D = np.linspace(eqfile['xgrid1'], eqfile['xgrid1'] + eqfile['xdim'], eqfile['nx']) + Z_1D = np.linspace(eqfile['zmid'] - eqfile['zdim']/2, eqfile['zmid'] + eqfile['zdim']/2, eqfile['nz']) + X, Z = np.meshgrid(X_1D, Z_1D, indexing='ij') + Xlcfs, Zlcfs = eqfile['xbdry'], eqfile['zbdry'] + + # Psi 2D grid defined on the Meshgrid + psi_eqdsk_2dgrid = eqfile['psi'] + # Create mask for the confined region, i.e.,Xlcfs.min() < X < Xlcfs.max(), Zlcfs.min() < Z < Zlcfs.max() + + offset = 0.01 + mask = (X > Xlcfs.min() - offset) & (X < Xlcfs.max() + offset) & (Z > Zlcfs.min() - offset) & (Z < Zlcfs.max() + offset) + masked_psi_eqdsk_2dgrid = np.ma.masked_where(~mask, psi_eqdsk_2dgrid) + + # q on uniform grid (pressure, etc., also defined here) + q_eqdsk_1dgrid = eqfile['qpsi'] + + # ---- Interpolations + q_interp = scipy.interpolate.interp1d(psi_eqdsk_1dgrid, eqfile['qpsi'], kind='cubic') + psi_spline_fit = scipy.interpolate.RectBivariateSpline(X_1D, Z_1D, psi_eqdsk_2dgrid, kx=3, ky=3, s=0) + F_interp = scipy.interpolate.interp1d(psi_eqdsk_1dgrid, eqfile['fpol'], kind='cubic') # toroidal field flux function + + # ----------------------------------------------------------- + # --------- Make flux surface contours --------- + # ----------------------------------------------------------- + + # set epsilon based on floating point precision of psi grid + # NOTE: this is hacky and should be replaced with a more robust method + epsilon = 1e-7 + + psi_interpolant = np.linspace(eqfile['psimag'] + epsilon, eqfile['psibdry'] - epsilon, 100) + + surfaces = [] + cg_psi = contour_generator(X, Z, masked_psi_eqdsk_2dgrid) + + for i, _psi in enumerate(psi_interpolant): + vertices = cg_psi.create_contour(_psi) + x_surface, z_surface = vertices[0].T[0], vertices[0].T[1] + surfaces.append((x_surface, z_surface)) + + + # ----------------------------------------------------------- + # --------- Compute Flux surface averages and 1D profiles --------- + # --- Area, Volume, R_inboard, R_outboard + # --- FSA: <1/R^2>, , <|grad(psi)|>, <|grad(psi)|^2> + # --- Toroidal plasma current + # --- Integral dl/Bp + # ----------------------------------------------------------- + + # Gathering area for profiles + areas, volumes = np.empty(len(surfaces)), np.empty(len(surfaces)) + R_inboard, R_outboard = np.empty(len(surfaces)), np.empty(len(surfaces)) + flux_surf_avg_1_over_R2_eqdsk = np.empty(len(surfaces)) # <1/R**2> + flux_surf_avg_Bp2_eqdsk = np.empty(len(surfaces)) # + flux_surf_avg_RBp_eqdsk = np.empty(len(surfaces)) # <|grad(psi)|> + flux_surf_avg_R2Bp2_eqdsk = np.empty(len(surfaces)) # <|grad(psi)|**2> + int_dl_over_Bp_eqdsk = np.empty(len(surfaces)) # int(Rdl / | grad(psi) |) + Ip_eqdsk = np.empty(len(surfaces)) # Toroidal plasma current + delta_upper_face_eqdsk = np.empty(len(surfaces)) # Upper face delta + delta_lower_face_eqdsk = np.empty(len(surfaces)) # Lower face delta + + # ---- Compute + for n, (x_surface, z_surface) in enumerate(surfaces): + surface_poloidal_angle = ((np.arctan2(z_surface - eqfile['zmag'], x_surface - eqfile['xmag'])) + np.pi) + + # dl, line elements on which we will integrate + surface_dl = np.sqrt(np.gradient(x_surface) ** 2 + np.gradient(z_surface) ** 2) + + # calculating gradient of psi in 2D + surface_dpsi_x = psi_spline_fit.ev(x_surface, z_surface, dx=1) + surface_dpsi_z = psi_spline_fit.ev(x_surface, z_surface, dy=1) + surface_abs_grad_psi = np.sqrt(surface_dpsi_x**2 + surface_dpsi_z**2) + + # Poloidal field strength Bp = |grad(psi)| / R + surface__Bpol = surface_abs_grad_psi / x_surface # / (2*np.pi) + surface_int_dl_over_bpol = np.sum(surface_dl / surface__Bpol) # This is denominator of all FSA + + # plasma current + surface_int_bpol_dl = np.sum(surface__Bpol * surface_dl) + + # 4 FSA, < 1/ R^2>, < | grad psi | >, < B_pol^2>, < | grad psi |^2 > + # where FSA(G) = int (G dl / Bpol) / (int (dl / Bpol)) + surface_FSA_int_one_over_r2 = np.sum(1 / x_surface ** 2 * surface_dl / surface__Bpol) / surface_int_dl_over_bpol + surface_FSA_abs_grad_psi = np.sum(surface_abs_grad_psi * surface_dl / surface__Bpol) / surface_int_dl_over_bpol + surface_FSA_Bpol_sqrd = np.sum(surface__Bpol * surface_dl) / surface_int_dl_over_bpol + surface_FSA_abs_grad_psi2 = np.sum(surface_abs_grad_psi ** 2 * surface_dl / surface__Bpol) / surface_int_dl_over_bpol + + # volumes and areas + area = calculate_area(x_surface, z_surface) + volume = area * 2 * np.pi * Rmaj + + # Triangularity + idx_upperextent = np.argmax(z_surface) + idx_lowerextent = np.argmin(z_surface) + + X_upperextent = x_surface[idx_upperextent] + X_lowerextent = x_surface[idx_lowerextent] + + # (RMAJ - X_upperextent) / RMIN + surface_delta_upper_face = (Rmaj - X_upperextent) / max(x_surface) + surface_delta_lower_face = (Rmaj - X_lowerextent) / max(x_surface) + + # Append to lists + areas[n] = area + volumes[n] = volume + R_inboard[n] = x_surface.min() + R_outboard[n] = x_surface.max() + int_dl_over_Bp_eqdsk[n] = surface_int_dl_over_bpol + flux_surf_avg_1_over_R2_eqdsk[n] = surface_FSA_int_one_over_r2 + flux_surf_avg_RBp_eqdsk[n] = surface_FSA_abs_grad_psi + flux_surf_avg_R2Bp2_eqdsk[n] = surface_FSA_abs_grad_psi2 + flux_surf_avg_Bp2_eqdsk[n] = surface_FSA_Bpol_sqrd + Ip_eqdsk[n] = surface_int_bpol_dl / constants.CONSTANTS.mu0 + delta_upper_face_eqdsk[n] = surface_delta_upper_face + delta_lower_face_eqdsk[n] = surface_delta_lower_face + + # q-profile on interpolation + q_profile = q_interp(psi_interpolant) + + # toroidal flux + Phi_eqdsk = scipy.integrate.cumulative_trapezoid(q_profile, psi_interpolant, initial=0.0) * 2*np.pi # / (2*np.pi) # factor of pi? + + # toroidal field flux function, T=RBphi + F_eqdsk = F_interp(psi_interpolant) + + # Triangularity of LCFS + idx_upperextent = np.argmax(Zlcfs) + idx_lowerextent = np.argmin(Zlcfs) + + X_upperextent = Xlcfs[idx_upperextent] + X_lowerextent = Xlcfs[idx_lowerextent] + + delta_upper_face = (Rmaj - X_upperextent) / Rmin + delta_lower_face = (Rmaj - X_lowerextent) / Rmin # Of LCFS + + rhon = np.sqrt(Phi_eqdsk / Phi_eqdsk[-1]) + vpr = 4*np.pi*Phi_eqdsk[-1] * rhon / F_eqdsk*flux_surf_avg_1_over_R2_eqdsk + + return cls( + Ip_from_parameters=Ip_from_parameters, + Rmaj=Rmaj, + Rmin=Rmin, + B=B0, + psi=psi_interpolant, + Ip_profile=Ip_eqdsk, + Phi=Phi_eqdsk, + Rin=R_inboard, + Rout=R_outboard, + F=F_eqdsk, + int_dl_over_Bp=int_dl_over_Bp_eqdsk, + flux_surf_avg_1_over_R2=flux_surf_avg_1_over_R2_eqdsk, + flux_surf_avg_RBp=flux_surf_avg_RBp_eqdsk, + flux_surf_avg_R2Bp2=flux_surf_avg_R2Bp2_eqdsk, + flux_surf_avg_Bp2=flux_surf_avg_Bp2_eqdsk, + delta_upper_face=delta_upper_face_eqdsk, + delta_lower_face=delta_lower_face_eqdsk, + vpr=vpr, + n_rho=n_rho, + hires_fac=hires_fac + ) + def build_standard_geometry( intermediate: StandardGeometryIntermediates, diff --git a/torax/geometry_loader.py b/torax/geometry_loader.py index ded12171..12622d46 100644 --- a/torax/geometry_loader.py +++ b/torax/geometry_loader.py @@ -19,6 +19,7 @@ import numpy as np import scipy +from eqdsk import EQDSKInterface # Internal import. @@ -28,6 +29,7 @@ class GeometrySource(enum.Enum): CHEASE = 0 FBT = 1 + EQDSK = 2 def _load_CHEASE_data( # pylint: disable=invalid-name @@ -59,6 +61,12 @@ def _load_fbt_data(file_path: str) -> dict[str, np.ndarray]: return scipy.io.loadmat(file_path, squeeze_me=True) +def _load_eqdsk_data(file_path: str) -> dict[str, np.ndarray]: + eqdsk_data = EQDSKInterface.from_file(file_path, no_cocos=True) + # TODO: handle COCOS shenanigans + return eqdsk_data.__dict__ # dict(eqdsk_data) + + def load_geo_data( geometry_dir: str | None, geometry_file: str, @@ -84,5 +92,9 @@ def load_geo_data( return _load_fbt_data( file_path=filepath ) + case GeometrySource.EQDSK: + return _load_eqdsk_data( + file_path=filepath + ) case _: raise ValueError(f'Unknown geometry source: {geometry_source}')