HyPar  1.0
Finite-Difference Hyperbolic-Parabolic PDE Solver on Cartesian Grids
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Interp1PrimFifthOrderHCWENOChar.c File Reference

Characteristic-based hybrid compact-WENO5 Scheme. More...

#include <stdio.h>
#include <basic.h>
#include <arrayfunctions.h>
#include <matmult_native.h>
#include <mathfunctions.h>
#include <interpolation.h>
#include <tridiagLU.h>
#include <mpivars.h>
#include <hypar.h>

Go to the source code of this file.

Macros

#define _MINIMUM_GHOSTS_   3
 

Functions

int Interp1PrimFifthOrderHCWENOChar (double *fI, double *fC, double *u, double *x, int upw, int dir, void *s, void *m, int uflag)
 5th order hybrid compact-WENO reconstruction (characteristic-based) on a uniform grid More...
 

Detailed Description

Characteristic-based hybrid compact-WENO5 Scheme.

Author
Debojyoti Ghosh

Definition in file Interp1PrimFifthOrderHCWENOChar.c.

Macro Definition Documentation

#define _MINIMUM_GHOSTS_   3

Minimum number of ghost points required for this interpolation method.

Definition at line 25 of file Interp1PrimFifthOrderHCWENOChar.c.

Function Documentation

int Interp1PrimFifthOrderHCWENOChar ( double *  fI,
double *  fC,
double *  u,
double *  x,
int  upw,
int  dir,
void *  s,
void *  m,
int  uflag 
)

5th order hybrid compact-WENO reconstruction (characteristic-based) on a uniform grid

Computes the interpolated values of the first primitive of a function \({\bf f}\left({\bf u}\right)\) at the interfaces from the cell-centered values of the function using the fifth hybrid compact-WENO order scheme on a uniform grid. The reconstruction is carried out in terms of

\begin{equation} \alpha^k = {\bf l}_k \cdot {\bf f},\ k=1,\cdots,n, \end{equation}

which is the \(k\)-th characteristic quantity, and \({\bf l}_k\) is the \(k\)-th left eigenvector, \({\bf r}_k\) is the \(k\)-th right eigenvector, and \(n\) is HyPar::nvars. The block tridiagonal system is solved using blocktridiagLU() (see also TridiagLU, tridiagLU.h). The final interpolated function is computed from the interpolated characteristic quantities as:

\begin{equation} \hat{\bf f}_{j+1/2} = \sum_{k=1}^n \alpha^k_{j+1/2} {\bf r}_k \end{equation}

See the references below for details of the hybrid compact-WENO scheme.

Implementation Notes:

  • This method assumes a uniform grid in the spatial dimension corresponding to the interpolation.
  • The method described above corresponds to a left-biased interpolation. The corresponding right-biased interpolation can be obtained by reflecting the equations about interface j+1/2.
  • The WENO weights are computed in WENOFifthOrderCalculateWeightsChar().
  • The left and right eigenvectors are computed at an averaged quantity at j+1/2. Thus, this function requires functions to compute the average state, and the left and right eigenvectors. These are provided by the physical model through

    If these functions are not provided by the physical model, then a characteristic-based interpolation cannot be used.

  • The function computes the interpolant for the entire grid in one call. It loops over all the grid lines along the interpolation direction and carries out the 1D interpolation along these grid lines.
  • Location of cell-centers and cell interfaces along the spatial dimension of the interpolation is shown in the following figure:
    chap1_1Ddomain.png

Function arguments:

Argument Type Explanation
fI double* Array to hold the computed interpolant at the grid interfaces. This array must have the same layout as the solution, but with no ghost points. Its size should be the same as u in all dimensions, except dir (the dimension along which to interpolate) along which it should be larger by 1 (number of interfaces is 1 more than the number of interior cell centers).
fC double* Array with the cell-centered values of the flux function \({\bf f}\left({\bf u}\right)\). This array must have the same layout and size as the solution, with ghost points.
u double* The solution array \({\bf u}\) (with ghost points). If the interpolation is characteristic based, this is needed to compute the eigendecomposition. For a multidimensional problem, the layout is as follows: u is a contiguous 1D array of size (nvars*dim[0]*dim[1]*...*dim[D-1]) corresponding to the multi-dimensional solution, with the following ordering - nvars, dim[0], dim[1], ..., dim[D-1], where nvars is the number of solution components (HyPar::nvars), dim is the local size (HyPar::dim_local), D is the number of spatial dimensions.
x double* The grid array (with ghost points). This is used only by non-uniform-grid interpolation methods. For multidimensional problems, the layout is as follows: x is a contiguous 1D array of size (dim[0]+dim[1]+...+dim[D-1]), with the spatial coordinates along dim[0] stored from 0,...,dim[0]-1, the spatial coordinates along dim[1] stored along dim[0],...,dim[0]+dim[1]-1, and so forth.
upw int Upwinding direction: if positive, a left-biased interpolant will be computed; if negative, a right-biased interpolant will be computed. If the interpolation method is central, then this has no effect.
dir int Spatial dimension along which to interpolate (eg: 0 for 1D; 0 or 1 for 2D; 0,1 or 2 for 3D)
s void* Solver object of type HyPar: the following variables are needed - HyPar::ghosts, HyPar::ndims, HyPar::nvars, HyPar::dim_local.
m void* MPI object of type MPIVariables: this is needed only by compact interpolation method that need to solve a global implicit system across MPI ranks.
uflag int A flag indicating if the function being interpolated \({\bf f}\) is the solution itself \({\bf u}\) (if 1, \({\bf f}\left({\bf u}\right) \equiv {\bf u}\)).

Reference:

  • Pirozzoli, S., Conservative Hybrid Compact-WENO Schemes for Shock-Turbulence Interaction, J. Comput. Phys., 178 (1), 2002, pp. 81-117, http://dx.doi.org/10.1006/jcph.2002.7021
  • Ren, Y.-X., Liu, M., Zhang, H., A characteristic-wise hybrid compact-WENO scheme for solving hyperbolic conservation laws, J. Comput. Phys., 192 (2), 2003, pp. 365-386,
Parameters
fIArray of interpolated function values at the interfaces
fCArray of cell-centered values of the function \({\bf f}\left({\bf u}\right)\)
uArray of cell-centered values of the solution \({\bf u}\)
xGrid coordinates
upwUpwind direction (left or right biased)
dirSpatial dimension along which to interpolation
sObject of type HyPar containing solver-related variables
mObject of type MPIVariables containing MPI-related variables
uflagFlag to indicate if \(f(u) \equiv u\), i.e, if the solution is being reconstructed

Definition at line 79 of file Interp1PrimFifthOrderHCWENOChar.c.

90 {
91  HyPar *solver = (HyPar*) s;
92  MPIVariables *mpi = (MPIVariables*) m;
93  CompactScheme *compact= (CompactScheme*) solver->compact;
94  WENOParameters *weno = (WENOParameters*) solver->interp;
95  TridiagLU *lu = (TridiagLU*) solver->lusolver;
96  int sys,Nsys,d,v,k;
98 
99  int ghosts = solver->ghosts;
100  int ndims = solver->ndims;
101  int nvars = solver->nvars;
102  int *dim = solver->dim_local;
103 
104  /* define some constants */
105  static const double one_half = 1.0/2.0;
106  static const double one_third = 1.0/3.0;
107  static const double one_sixth = 1.0/6.0;
108 
109  double *ww1, *ww2, *ww3;
110  ww1 = weno->w1 + (upw < 0 ? 2*weno->size : 0) + (uflag ? weno->size : 0) + weno->offset[dir];
111  ww2 = weno->w2 + (upw < 0 ? 2*weno->size : 0) + (uflag ? weno->size : 0) + weno->offset[dir];
112  ww3 = weno->w3 + (upw < 0 ? 2*weno->size : 0) + (uflag ? weno->size : 0) + weno->offset[dir];
113 
114  /* create index and bounds for the outer loop, i.e., to loop over all 1D lines along
115  dimension "dir" */
116  int indexC[ndims], indexI[ndims], index_outer[ndims], bounds_outer[ndims], bounds_inter[ndims];
117  _ArrayCopy1D_(dim,bounds_outer,ndims); bounds_outer[dir] = 1;
118  _ArrayCopy1D_(dim,bounds_inter,ndims); bounds_inter[dir] += 1;
119 
120  /* calculate total number of block tridiagonal systems to solve */
121  _ArrayProduct1D_(bounds_outer,ndims,Nsys);
122 
123  /* allocate arrays for the averaged state, eigenvectors and characteristic interpolated f */
124  double R[nvars*nvars], L[nvars*nvars], uavg[nvars];
125 
126  /* Allocate arrays for tridiagonal system */
127  double *A = compact->A;
128  double *B = compact->B;
129  double *C = compact->C;
130  double *F = compact->R;
131 
132 #pragma omp parallel for schedule(auto) default(shared) private(sys,d,v,k,R,L,uavg,index_outer,indexC,indexI)
133  for (sys=0; sys<Nsys; sys++) {
134  _ArrayIndexnD_(ndims,sys,bounds_outer,index_outer,0);
135  _ArrayCopy1D_(index_outer,indexC,ndims);
136  _ArrayCopy1D_(index_outer,indexI,ndims);
137  for (indexI[dir] = 0; indexI[dir] < dim[dir]+1; indexI[dir]++) {
138  int qm1,qm2,qm3,qp1,qp2;
139  if (upw > 0) {
140  indexC[dir] = indexI[dir]-3; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qm3);
141  indexC[dir] = indexI[dir]-2; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qm2);
142  indexC[dir] = indexI[dir]-1; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qm1);
143  indexC[dir] = indexI[dir] ; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qp1);
144  indexC[dir] = indexI[dir]+1; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qp2);
145  } else {
146  indexC[dir] = indexI[dir]+2; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qm3);
147  indexC[dir] = indexI[dir]+1; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qm2);
148  indexC[dir] = indexI[dir] ; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qm1);
149  indexC[dir] = indexI[dir]-1; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qp1);
150  indexC[dir] = indexI[dir]-2; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qp2);
151  }
152 
153  int p; /* 1D index of the interface */
154  _ArrayIndex1D_(ndims,bounds_inter,indexI,0,p);
155 
156  /* find averaged state at this interface */
157  IERR solver->AveragingFunction(uavg,&u[nvars*qm1],&u[nvars*qp1],solver->physics); CHECKERR(ierr);
158 
159  /* Get the left and right eigenvectors */
160  IERR solver->GetLeftEigenvectors (uavg,L,solver->physics,dir); CHECKERR(ierr);
161  IERR solver->GetRightEigenvectors (uavg,R,solver->physics,dir); CHECKERR(ierr);
162 
163  for (v=0; v<nvars; v++) {
164 
165  /* calculate the characteristic flux components along this characteristic */
166  double fm3, fm2, fm1, fp1, fp2;
167  fm3 = fm2 = fm1 = fp1 = fp2 = 0;
168  for (k = 0; k < nvars; k++) {
169  fm3 += L[v*nvars+k] * fC[qm3*nvars+k];
170  fm2 += L[v*nvars+k] * fC[qm2*nvars+k];
171  fm1 += L[v*nvars+k] * fC[qm1*nvars+k];
172  fp1 += L[v*nvars+k] * fC[qp1*nvars+k];
173  fp2 += L[v*nvars+k] * fC[qp2*nvars+k];
174  }
175 
176  /* Candidate stencils and their optimal weights*/
177  double f1, f2, f3;
178  if ( ((mpi->ip[dir] == 0 ) && (indexI[dir] == 0 ))
179  || ((mpi->ip[dir] == mpi->iproc[dir]-1) && (indexI[dir] == dim[dir])) ) {
180  /* Use WENO5 at the physical boundaries */
181  f1 = (2*one_sixth)*fm3 - (7.0*one_sixth)*fm2 + (11.0*one_sixth)*fm1;
182  f2 = (-one_sixth)*fm2 + (5.0*one_sixth)*fm1 + (2*one_sixth)*fp1;
183  f3 = (2*one_sixth)*fm1 + (5*one_sixth)*fp1 - (one_sixth)*fp2;
184  } else {
185  /* HCWENO5 at the interior points */
186  f1 = (one_sixth) * (fm2 + 5*fm1);
187  f2 = (one_sixth) * (5*fm1 + fp1);
188  f3 = (one_sixth) * (fm1 + 5*fp1);
189  }
190 
191  /* calculate WENO weights */
192  double w1,w2,w3;
193  w1 = *(ww1+p*nvars+v);
194  w2 = *(ww2+p*nvars+v);
195  w3 = *(ww3+p*nvars+v);
196 
197  /* calculate the hybridization parameter */
198  double sigma;
199  if ( ((mpi->ip[dir] == 0 ) && (indexI[dir] == 0 ))
200  || ((mpi->ip[dir] == mpi->iproc[dir]-1) && (indexI[dir] == dim[dir])) ) {
201  /* Standard WENO at physical boundaries */
202  sigma = 0.0;
203  } else {
204  double cuckoo, df_jm12, df_jp12, df_jp32, r_j, r_jp1, r_int;
205  cuckoo = (0.9*weno->rc / (1.0-0.9*weno->rc)) * weno->xi * weno->xi;
206  df_jm12 = fm1 - fm2;
207  df_jp12 = fp1 - fm1;
208  df_jp32 = fp2 - fp1;
209  r_j = (absolute(2*df_jp12*df_jm12)+cuckoo)/(df_jp12*df_jp12+df_jm12*df_jm12+cuckoo);
210  r_jp1 = (absolute(2*df_jp32*df_jp12)+cuckoo)/(df_jp32*df_jp32+df_jp12*df_jp12+cuckoo);
211  r_int = min(r_j, r_jp1);
212  sigma = min((r_int/weno->rc), 1.0);
213  }
214 
215  if (upw > 0) {
216  for (k=0; k<nvars; k++) {
217  A[(Nsys*indexI[dir]+sys)*nvars*nvars+v*nvars+k] = (one_half*sigma) * L[v*nvars+k];
218  B[(Nsys*indexI[dir]+sys)*nvars*nvars+v*nvars+k] = (1.0) * L[v*nvars+k];
219  C[(Nsys*indexI[dir]+sys)*nvars*nvars+v*nvars+k] = (one_sixth*sigma) * L[v*nvars+k];
220  }
221  } else {
222  for (k=0; k<nvars; k++) {
223  C[(Nsys*indexI[dir]+sys)*nvars*nvars+v*nvars+k] = (one_half*sigma) * L[v*nvars+k];
224  B[(Nsys*indexI[dir]+sys)*nvars*nvars+v*nvars+k] = (1.0) * L[v*nvars+k];
225  A[(Nsys*indexI[dir]+sys)*nvars*nvars+v*nvars+k] = (one_sixth*sigma) * L[v*nvars+k];
226  }
227  }
228  double fWENO, fCompact;
229  fWENO = w1*f1 + w2*f2 + w3*f3;
230  fCompact = one_sixth * (one_third*fm2 + 19.0*one_third*fm1 + 10.0*one_third*fp1);
231  F[(Nsys*indexI[dir]+sys)*nvars+v] = sigma*fCompact + (1.0-sigma)*fWENO;
232  }
233  }
234  }
235 
236 #ifdef serial
237 
238  /* Solve the tridiagonal system */
239  IERR blocktridiagLU(A,B,C,F,dim[dir]+1,Nsys,nvars,lu,NULL); CHECKERR(ierr);
240 
241 #else
242 
243  /* Solve the tridiagonal system */
244  /* all processes except the last will solve without the last interface to avoid overlap */
245  if (mpi->ip[dir] != mpi->iproc[dir]-1) {
246  IERR blocktridiagLU(A,B,C,F,dim[dir] ,Nsys,nvars,lu,&mpi->comm[dir]); CHECKERR(ierr);
247  } else {
248  IERR blocktridiagLU(A,B,C,F,dim[dir]+1,Nsys,nvars,lu,&mpi->comm[dir]); CHECKERR(ierr);
249  }
250 
251  /* Now get the solution to the last interface from the next proc */
252  double *sendbuf = compact->sendbuf;
253  double *recvbuf = compact->recvbuf;
254  MPI_Request req[2] = {MPI_REQUEST_NULL,MPI_REQUEST_NULL};
255  if (mpi->ip[dir]) for (d=0; d<Nsys*nvars; d++) sendbuf[d] = F[d];
256  if (mpi->ip[dir] != mpi->iproc[dir]-1) MPI_Irecv(recvbuf,Nsys*nvars,MPI_DOUBLE,mpi->ip[dir]+1,214,mpi->comm[dir],&req[0]);
257  if (mpi->ip[dir]) MPI_Isend(sendbuf,Nsys*nvars,MPI_DOUBLE,mpi->ip[dir]-1,214,mpi->comm[dir],&req[1]);
258  MPI_Status status_arr[2];
259  MPI_Waitall(2,&req[0],status_arr);
260  if (mpi->ip[dir] != mpi->iproc[dir]-1) for (d=0; d<Nsys*nvars; d++) F[d+Nsys*nvars*dim[dir]] = recvbuf[d];
261 
262 #endif
263 
264  /* save the solution to fI */
265 #pragma omp parallel for schedule(auto) default(shared) private(sys,d,v,k,R,L,uavg,index_outer,indexC,indexI)
266  for (sys=0; sys<Nsys; sys++) {
267  _ArrayIndexnD_(ndims,sys,bounds_outer,index_outer,0);
268  _ArrayCopy1D_(index_outer,indexI,ndims);
269  for (indexI[dir] = 0; indexI[dir] < dim[dir]+1; indexI[dir]++) {
270  int p; _ArrayIndex1D_(ndims,bounds_inter,indexI,0,p);
271  _ArrayCopy1D_((F+sys*nvars+Nsys*nvars*indexI[dir]),(fI+nvars*p),nvars);
272  }
273  }
274 
275  return(0);
276 }
void * interp
Definition: hypar.h:362
MPI_Comm * comm
#define _ArrayIndexnD_(N, index, imax, i, ghost)
void * physics
Definition: hypar.h:266
int(* GetRightEigenvectors)(double *, double *, void *, int)
Definition: hypar.h:359
int * dim_local
Definition: hypar.h:37
int blocktridiagLU(double *, double *, double *, double *, int, int, int, void *, void *)
double * recvbuf
Structure of variables/parameters needed by the WENO-type scheme.
Structure of variables/parameters needed by the compact schemes.
int ghosts
Definition: hypar.h:52
#define _ArrayIndex1D_(N, imax, i, ghost, index)
int(* AveragingFunction)(double *, double *, double *, void *)
Definition: hypar.h:354
void * compact
Definition: hypar.h:364
int(* GetLeftEigenvectors)(double *, double *, void *, int)
Definition: hypar.h:357
#define _ArrayCopy1D_(x, y, size)
int nvars
Definition: hypar.h:29
#define CHECKERR(ierr)
Definition: basic.h:18
int ndims
Definition: hypar.h:26
#define absolute(a)
Definition: math_ops.h:32
#define IERR
Definition: basic.h:16
#define _ArrayProduct1D_(x, size, p)
Structure of MPI-related variables.
Structure containing all solver-specific variables and functions.
Definition: hypar.h:23
double * sendbuf
void * lusolver
Definition: hypar.h:368
#define min(a, b)
Definition: math_ops.h:14
#define _DECLARE_IERR_
Definition: basic.h:17