1 // SPDX-FileCopyrightText: Copyright (c) 2017-2024, HONEE contributors. 2 // SPDX-License-Identifier: Apache-2.0 OR BSD-2-Clause 3 4 /// @file 5 /// Structs and helper functions for training data-driven subgrid-stress models 6 /// See 'Invariant data-driven subgrid stress modeling in the strain-rate eigenframe for large eddy simulation' 2022 and 'S-frame discrepancy 7 /// correction models for data-informed Reynolds stress closure' 2022 8 #include <ceed/types.h> 9 10 #include "differential_filter_enums.h" 11 #include "newtonian_state.h" 12 #include "newtonian_types.h" 13 #include "sgs_dd_utils.h" 14 #include "utils.h" 15 #include "utils_eigensolver_jacobi.h" 16 17 typedef struct SGS_DD_TrainingContext_ *SGS_DDTrainingContext; 18 struct SGS_DD_TrainingContext_ { 19 struct NewtonianIdealGasContext_ gas; 20 }; 21 22 // @brief Calculate Data-Driven SGS model training data at nodes 23 CEED_QFUNCTION_HELPER int ComputeSGS_DDAnisotropicTrainingDataNodal(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out, 24 StateVariable state_var) { 25 const CeedScalar(*q)[CEED_Q_VLA] = (const CeedScalar(*)[CEED_Q_VLA])in[0]; 26 const CeedScalar(*velo_prod)[CEED_Q_VLA] = (const CeedScalar(*)[CEED_Q_VLA])in[1]; 27 const CeedScalar(*grad_velo)[3][CEED_Q_VLA] = (const CeedScalar(*)[3][CEED_Q_VLA])in[2]; 28 const CeedScalar(*A_ij_delta)[CEED_Q_VLA] = (const CeedScalar(*)[CEED_Q_VLA])in[3]; 29 const CeedScalar(*inv_multiplicity) = (const CeedScalar(*))in[4]; 30 CeedScalar(*v)[CEED_Q_VLA] = (CeedScalar(*)[CEED_Q_VLA])out[0]; 31 32 const SGS_DDTrainingContext sgsdd_ctx = (SGS_DDTrainingContext)ctx; 33 const NewtonianIdealGasContext gas = &sgsdd_ctx->gas; 34 35 CeedPragmaSIMD for (CeedInt i = 0; i < Q; i++) { 36 const CeedScalar qi[5] = {q[0][i], q[1][i], q[2][i], q[3][i], q[4][i]}; 37 const CeedScalar grad_velo_aniso[3][3] = { 38 {grad_velo[0][0][i], grad_velo[0][1][i], grad_velo[0][2][i]}, 39 {grad_velo[1][0][i], grad_velo[1][1][i], grad_velo[1][2][i]}, 40 {grad_velo[2][0][i], grad_velo[2][1][i], grad_velo[2][2][i]} 41 }; 42 const CeedScalar km_A_ij[6] = {A_ij_delta[0][i], A_ij_delta[1][i], A_ij_delta[2][i], A_ij_delta[3][i], A_ij_delta[4][i], A_ij_delta[5][i]}; 43 const CeedScalar delta = A_ij_delta[6][i]; 44 const State s = StateFromQ(gas, qi, state_var); 45 CeedScalar inputs[6]; 46 CeedScalar eigenvectors[3][3], grad_velo_magnitude; // dummy variables, don't actually use them 47 48 ComputeSgsDDInputs(grad_velo_aniso, km_A_ij, delta, gas->mu / s.U.density, eigenvectors, inputs, &grad_velo_magnitude); 49 50 for (int j = 0; j < 6; j++) v[j][i] = inv_multiplicity[i] * inputs[j]; 51 52 v[0 + 6][i] = (velo_prod[DIFF_FILTER_VELOCITY_SQUARED_XX][i] - Square(s.Y.velocity[0])) * inv_multiplicity[i]; 53 v[1 + 6][i] = (velo_prod[DIFF_FILTER_VELOCITY_SQUARED_YY][i] - Square(s.Y.velocity[1])) * inv_multiplicity[i]; 54 v[2 + 6][i] = (velo_prod[DIFF_FILTER_VELOCITY_SQUARED_ZZ][i] - Square(s.Y.velocity[2])) * inv_multiplicity[i]; 55 v[3 + 6][i] = (velo_prod[DIFF_FILTER_VELOCITY_SQUARED_YZ][i] - s.Y.velocity[1] * s.Y.velocity[2]) * inv_multiplicity[i]; 56 v[4 + 6][i] = (velo_prod[DIFF_FILTER_VELOCITY_SQUARED_XZ][i] - s.Y.velocity[0] * s.Y.velocity[2]) * inv_multiplicity[i]; 57 v[5 + 6][i] = (velo_prod[DIFF_FILTER_VELOCITY_SQUARED_XY][i] - s.Y.velocity[0] * s.Y.velocity[1]) * inv_multiplicity[i]; 58 } 59 return 0; 60 } 61 62 CEED_QFUNCTION(ComputeSGS_DDAnisotropicTrainingDataNodal_Prim)(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out) { 63 return ComputeSGS_DDAnisotropicTrainingDataNodal(ctx, Q, in, out, STATEVAR_PRIMITIVE); 64 } 65