Date: 2025-03-29T05:58:49+00:00

Actual source code: alpha2.c

      1: /*
      2:   Code for timestepping with implicit generalized-\alpha method
      3:   for second order systems.
      4: */
      5: #include <petsc/private/tsimpl.h>

      7: static PetscBool  cited      = PETSC_FALSE;
      8: static const char citation[] = "@article{Chung1993,\n"
      9:                                "  title   = {A Time Integration Algorithm for Structural Dynamics with Improved Numerical Dissipation: The Generalized-$\\alpha$ Method},\n"
     10:                                "  author  = {J. Chung, G. M. Hubert},\n"
     11:                                "  journal = {ASME Journal of Applied Mechanics},\n"
     12:                                "  volume  = {60},\n"
     13:                                "  number  = {2},\n"
     14:                                "  pages   = {371--375},\n"
     15:                                "  year    = {1993},\n"
     16:                                "  issn    = {0021-8936},\n"
     17:                                "  doi     = {http://dx.doi.org/10.1115/1.2900803}\n}\n";

     19: typedef struct {
     20:   PetscReal stage_time;
     21:   PetscReal shift_V;
     22:   PetscReal shift_A;
     23:   PetscReal scale_F;
     24:   Vec       X0, Xa, X1;
     25:   Vec       V0, Va, V1;
     26:   Vec       A0, Aa, A1;

     28:   Vec vec_dot;

     30:   PetscReal Alpha_m;
     31:   PetscReal Alpha_f;
     32:   PetscReal Gamma;
     33:   PetscReal Beta;
     34:   PetscInt  order;

     36:   Vec vec_sol_prev;
     37:   Vec vec_dot_prev;
     38:   Vec vec_lte_work[2];

     40:   TSStepStatus status;

     42:   TSAlpha2PredictorFn *predictor;
     43:   void                *predictor_ctx;
     44: } TS_Alpha;

     46: /*@C
     47:   TSAlpha2SetPredictor - sets the callback for computing a predictor (i.e., initial guess
     48:   for the nonlinear solver).

     50:   Input Parameters:
     51: + ts        - timestepping context
     52: . predictor - callback to set the predictor in each step
     53: - ctx       - the application context, which may be set to `NULL` if not used

     55:   Level: intermediate

     57:   Notes:

     59:   If this function is never called, a same-state-vector predictor will be used, i.e.,
     60:   the initial guess will be the converged solution from the previous time step, without regard
     61:   for the previous velocity or acceleration.

     63: .seealso: [](ch_ts), `TS`, `TSALPHA2`, `TSAlpha2PredictorFn`
     64: @*/
     65: PetscErrorCode TSAlpha2SetPredictor(TS ts, TSAlpha2PredictorFn *predictor, void *ctx)
     66: {
     67:   TS_Alpha *th = (TS_Alpha *)ts->data;

     69:   PetscFunctionBegin;
     70:   th->predictor     = predictor;
     71:   th->predictor_ctx = ctx;
     72:   PetscFunctionReturn(PETSC_SUCCESS);
     73: }

     75: static PetscErrorCode TSAlpha_ApplyPredictor(TS ts, Vec X1)
     76: {
     77:   /* Apply a custom predictor if set, or default to same-displacement. */
     78:   TS_Alpha *th = (TS_Alpha *)ts->data;

     80:   PetscFunctionBegin;
     81:   if (th->predictor) PetscCall(th->predictor(ts, th->X0, th->V0, th->A0, X1, th->predictor_ctx));
     82:   else PetscCall(VecCopy(th->X0, X1));
     83:   PetscFunctionReturn(PETSC_SUCCESS);
     84: }

     86: static PetscErrorCode TSAlpha_StageTime(TS ts)
     87: {
     88:   TS_Alpha *th      = (TS_Alpha *)ts->data;
     89:   PetscReal t       = ts->ptime;
     90:   PetscReal dt      = ts->time_step;
     91:   PetscReal Alpha_m = th->Alpha_m;
     92:   PetscReal Alpha_f = th->Alpha_f;
     93:   PetscReal Gamma   = th->Gamma;
     94:   PetscReal Beta    = th->Beta;

     96:   PetscFunctionBegin;
     97:   th->stage_time = t + Alpha_f * dt;
     98:   th->shift_V    = Gamma / (dt * Beta);
     99:   th->shift_A    = Alpha_m / (Alpha_f * dt * dt * Beta);
    100:   th->scale_F    = 1 / Alpha_f;
    101:   PetscFunctionReturn(PETSC_SUCCESS);
    102: }

    104: static PetscErrorCode TSAlpha_StageVecs(TS ts, Vec X)
    105: {
    106:   TS_Alpha *th = (TS_Alpha *)ts->data;
    107:   Vec       X1 = X, V1 = th->V1, A1 = th->A1;
    108:   Vec       Xa = th->Xa, Va = th->Va, Aa = th->Aa;
    109:   Vec       X0 = th->X0, V0 = th->V0, A0 = th->A0;
    110:   PetscReal dt      = ts->time_step;
    111:   PetscReal Alpha_m = th->Alpha_m;
    112:   PetscReal Alpha_f = th->Alpha_f;
    113:   PetscReal Gamma   = th->Gamma;
    114:   PetscReal Beta    = th->Beta;

    116:   PetscFunctionBegin;
    117:   /* A1 = ... */
    118:   PetscCall(VecWAXPY(A1, -1.0, X0, X1));
    119:   PetscCall(VecAXPY(A1, -dt, V0));
    120:   PetscCall(VecAXPBY(A1, -(1 - 2 * Beta) / (2 * Beta), 1 / (dt * dt * Beta), A0));
    121:   /* V1 = ... */
    122:   PetscCall(VecWAXPY(V1, (1.0 - Gamma) / Gamma, A0, A1));
    123:   PetscCall(VecAYPX(V1, dt * Gamma, V0));
    124:   /* Xa = X0 + Alpha_f*(X1-X0) */
    125:   PetscCall(VecWAXPY(Xa, -1.0, X0, X1));
    126:   PetscCall(VecAYPX(Xa, Alpha_f, X0));
    127:   /* Va = V0 + Alpha_f*(V1-V0) */
    128:   PetscCall(VecWAXPY(Va, -1.0, V0, V1));
    129:   PetscCall(VecAYPX(Va, Alpha_f, V0));
    130:   /* Aa = A0 + Alpha_m*(A1-A0) */
    131:   PetscCall(VecWAXPY(Aa, -1.0, A0, A1));
    132:   PetscCall(VecAYPX(Aa, Alpha_m, A0));
    133:   PetscFunctionReturn(PETSC_SUCCESS);
    134: }

    136: static PetscErrorCode TSAlpha_SNESSolve(TS ts, Vec b, Vec x)
    137: {
    138:   PetscInt nits, lits;

    140:   PetscFunctionBegin;
    141:   PetscCall(SNESSolve(ts->snes, b, x));
    142:   PetscCall(SNESGetIterationNumber(ts->snes, &nits));
    143:   PetscCall(SNESGetLinearSolveIterations(ts->snes, &lits));
    144:   ts->snes_its += nits;
    145:   ts->ksp_its += lits;
    146:   PetscFunctionReturn(PETSC_SUCCESS);
    147: }

    149: /*
    150:   Compute a consistent initial state for the generalized-alpha method.
    151:   - Solve two successive first-order-accurate steps with halved time step.
    152:   - Compute the initial second time derivative using backward differences.
    153:   - If using adaptivity, estimate the LTE of the initial step.
    154: */
    155: static PetscErrorCode TSAlpha_Restart(TS ts, PetscBool *initok)
    156: {
    157:   TS_Alpha *th = (TS_Alpha *)ts->data;
    158:   PetscReal time_step;
    159:   PetscReal alpha_m, alpha_f, gamma, beta;
    160:   Vec       X0 = ts->vec_sol, X1, X2 = th->X1;
    161:   Vec       V0 = ts->vec_dot, V1, V2 = th->V1;
    162:   PetscBool stageok;

    164:   PetscFunctionBegin;
    165:   PetscCall(VecDuplicate(X0, &X1));
    166:   PetscCall(VecDuplicate(V0, &V1));

    168:   /* Setup first-order-accurate method with halved time step */
    169:   PetscCall(TSAlpha2GetParams(ts, &alpha_m, &alpha_f, &gamma, &beta));
    170:   PetscCall(TSAlpha2SetParams(ts, 1, 1, 1, 0.5));
    171:   PetscCall(TSGetTimeStep(ts, &time_step));
    172:   ts->time_step = time_step / 2;
    173:   PetscCall(TSAlpha_StageTime(ts));
    174:   th->stage_time = ts->ptime;
    175:   PetscCall(VecZeroEntries(th->A0));

    177:   /* First half step, (t0,X0,V0) -> (t1,X1,V1) */
    178:   th->stage_time += ts->time_step;
    179:   PetscCall(VecCopy(X0, th->X0));
    180:   PetscCall(VecCopy(V0, th->V0));
    181:   PetscCall(TSPreStage(ts, th->stage_time));
    182:   PetscCall(TSAlpha_ApplyPredictor(ts, X1));
    183:   PetscCall(TSAlpha_SNESSolve(ts, NULL, X1));
    184:   PetscCall(VecCopy(th->V1, V1));
    185:   PetscCall(TSPostStage(ts, th->stage_time, 0, &X1));
    186:   PetscCall(TSAdaptCheckStage(ts->adapt, ts, th->stage_time, X1, &stageok));
    187:   if (!stageok) goto finally;

    189:   /* Second half step, (t1,X1,V1) -> (t2,X2,V2) */
    190:   th->stage_time += ts->time_step;
    191:   PetscCall(VecCopy(X1, th->X0));
    192:   PetscCall(VecCopy(V1, th->V0));
    193:   PetscCall(TSPreStage(ts, th->stage_time));
    194:   PetscCall(TSAlpha_ApplyPredictor(ts, X2));
    195:   PetscCall(TSAlpha_SNESSolve(ts, NULL, X2));
    196:   PetscCall(VecCopy(th->V1, V2));
    197:   PetscCall(TSPostStage(ts, th->stage_time, 0, &X2));
    198:   PetscCall(TSAdaptCheckStage(ts->adapt, ts, th->stage_time, X2, &stageok));
    199:   if (!stageok) goto finally;

    201:   /* Compute A0 ~ dV/dt at t0 with backward differences */
    202:   PetscCall(VecZeroEntries(th->A0));
    203:   PetscCall(VecAXPY(th->A0, -3 / time_step, V0));
    204:   PetscCall(VecAXPY(th->A0, +4 / time_step, V1));
    205:   PetscCall(VecAXPY(th->A0, -1 / time_step, V2));

    207:   /* Rough, lower-order estimate LTE of the initial step */
    208:   if (th->vec_lte_work[0]) {
    209:     PetscCall(VecZeroEntries(th->vec_lte_work[0]));
    210:     PetscCall(VecAXPY(th->vec_lte_work[0], +2, X2));
    211:     PetscCall(VecAXPY(th->vec_lte_work[0], -4, X1));
    212:     PetscCall(VecAXPY(th->vec_lte_work[0], +2, X0));
    213:   }
    214:   if (th->vec_lte_work[1]) {
    215:     PetscCall(VecZeroEntries(th->vec_lte_work[1]));
    216:     PetscCall(VecAXPY(th->vec_lte_work[1], +2, V2));
    217:     PetscCall(VecAXPY(th->vec_lte_work[1], -4, V1));
    218:     PetscCall(VecAXPY(th->vec_lte_work[1], +2, V0));
    219:   }

    221: finally:
    222:   /* Revert TSAlpha to the initial state (t0,X0,V0), but retain
    223:      potential time step reduction by factor after failed solve. */
    224:   if (initok) *initok = stageok;
    225:   PetscCall(TSSetTimeStep(ts, 2 * ts->time_step));
    226:   PetscCall(TSAlpha2SetParams(ts, alpha_m, alpha_f, gamma, beta));
    227:   PetscCall(VecCopy(ts->vec_sol, th->X0));
    228:   PetscCall(VecCopy(ts->vec_dot, th->V0));

    230:   PetscCall(VecDestroy(&X1));
    231:   PetscCall(VecDestroy(&V1));
    232:   PetscFunctionReturn(PETSC_SUCCESS);
    233: }

    235: static PetscErrorCode TSStep_Alpha(TS ts)
    236: {
    237:   TS_Alpha *th         = (TS_Alpha *)ts->data;
    238:   PetscInt  rejections = 0;
    239:   PetscBool stageok, accept = PETSC_TRUE;
    240:   PetscReal next_time_step = ts->time_step;

    242:   PetscFunctionBegin;
    243:   PetscCall(PetscCitationsRegister(citation, &cited));

    245:   if (!ts->steprollback) {
    246:     if (th->vec_sol_prev) PetscCall(VecCopy(th->X0, th->vec_sol_prev));
    247:     if (th->vec_dot_prev) PetscCall(VecCopy(th->V0, th->vec_dot_prev));
    248:     PetscCall(VecCopy(ts->vec_sol, th->X0));
    249:     PetscCall(VecCopy(ts->vec_dot, th->V0));
    250:     PetscCall(VecCopy(th->A1, th->A0));
    251:   }

    253:   th->status = TS_STEP_INCOMPLETE;
    254:   while (!ts->reason && th->status != TS_STEP_COMPLETE) {
    255:     if (ts->steprestart) {
    256:       PetscCall(TSAlpha_Restart(ts, &stageok));
    257:       if (!stageok) goto reject_step;
    258:     }

    260:     PetscCall(TSAlpha_StageTime(ts));
    261:     PetscCall(TSAlpha_ApplyPredictor(ts, th->X1));
    262:     PetscCall(TSPreStage(ts, th->stage_time));
    263:     PetscCall(TSAlpha_SNESSolve(ts, NULL, th->X1));
    264:     PetscCall(TSPostStage(ts, th->stage_time, 0, &th->Xa));
    265:     PetscCall(TSAdaptCheckStage(ts->adapt, ts, th->stage_time, th->Xa, &stageok));
    266:     if (!stageok) goto reject_step;

    268:     th->status = TS_STEP_PENDING;
    269:     PetscCall(VecCopy(th->X1, ts->vec_sol));
    270:     PetscCall(VecCopy(th->V1, ts->vec_dot));
    271:     PetscCall(TSAdaptChoose(ts->adapt, ts, ts->time_step, NULL, &next_time_step, &accept));
    272:     th->status = accept ? TS_STEP_COMPLETE : TS_STEP_INCOMPLETE;
    273:     if (!accept) {
    274:       PetscCall(VecCopy(th->X0, ts->vec_sol));
    275:       PetscCall(VecCopy(th->V0, ts->vec_dot));
    276:       ts->time_step = next_time_step;
    277:       goto reject_step;
    278:     }

    280:     ts->ptime += ts->time_step;
    281:     ts->time_step = next_time_step;
    282:     break;

    284:   reject_step:
    285:     ts->reject++;
    286:     accept = PETSC_FALSE;
    287:     if (!ts->reason && ++rejections > ts->max_reject && ts->max_reject >= 0) {
    288:       ts->reason = TS_DIVERGED_STEP_REJECTED;
    289:       PetscCall(PetscInfo(ts, "Step=%" PetscInt_FMT ", step rejections %" PetscInt_FMT " greater than current TS allowed, stopping solve\n", ts->steps, rejections));
    290:     }
    291:   }
    292:   PetscFunctionReturn(PETSC_SUCCESS);
    293: }

    295: static PetscErrorCode TSEvaluateWLTE_Alpha(TS ts, NormType wnormtype, PetscInt *order, PetscReal *wlte)
    296: {
    297:   TS_Alpha *th = (TS_Alpha *)ts->data;
    298:   Vec       X  = th->X1;              /* X = solution */
    299:   Vec       V  = th->V1;              /* V = solution */
    300:   Vec       Y  = th->vec_lte_work[0]; /* Y = X + LTE  */
    301:   Vec       Z  = th->vec_lte_work[1]; /* Z = V + LTE  */
    302:   PetscReal enormX, enormV, enormXa, enormVa, enormXr, enormVr;

    304:   PetscFunctionBegin;
    305:   if (!th->vec_sol_prev) {
    306:     *wlte = -1;
    307:     PetscFunctionReturn(PETSC_SUCCESS);
    308:   }
    309:   if (!th->vec_dot_prev) {
    310:     *wlte = -1;
    311:     PetscFunctionReturn(PETSC_SUCCESS);
    312:   }
    313:   if (!th->vec_lte_work[0]) {
    314:     *wlte = -1;
    315:     PetscFunctionReturn(PETSC_SUCCESS);
    316:   }
    317:   if (!th->vec_lte_work[1]) {
    318:     *wlte = -1;
    319:     PetscFunctionReturn(PETSC_SUCCESS);
    320:   }
    321:   if (ts->steprestart) {
    322:     /* th->vec_lte_prev is set to the LTE in TSAlpha_Restart() */
    323:     PetscCall(VecAXPY(Y, 1, X));
    324:     PetscCall(VecAXPY(Z, 1, V));
    325:   } else {
    326:     /* Compute LTE using backward differences with non-constant time step */
    327:     PetscReal   h = ts->time_step, h_prev = ts->ptime - ts->ptime_prev;
    328:     PetscReal   a = 1 + h_prev / h;
    329:     PetscScalar scal[3];
    330:     Vec         vecX[3], vecV[3];
    331:     scal[0] = +1 / a;
    332:     scal[1] = -1 / (a - 1);
    333:     scal[2] = +1 / (a * (a - 1));
    334:     vecX[0] = th->X1;
    335:     vecX[1] = th->X0;
    336:     vecX[2] = th->vec_sol_prev;
    337:     vecV[0] = th->V1;
    338:     vecV[1] = th->V0;
    339:     vecV[2] = th->vec_dot_prev;
    340:     PetscCall(VecCopy(X, Y));
    341:     PetscCall(VecMAXPY(Y, 3, scal, vecX));
    342:     PetscCall(VecCopy(V, Z));
    343:     PetscCall(VecMAXPY(Z, 3, scal, vecV));
    344:   }
    345:   /* XXX ts->atol and ts->vatol are not appropriate for computing enormV */
    346:   PetscCall(TSErrorWeightedNorm(ts, X, Y, wnormtype, &enormX, &enormXa, &enormXr));
    347:   PetscCall(TSErrorWeightedNorm(ts, V, Z, wnormtype, &enormV, &enormVa, &enormVr));
    348:   if (wnormtype == NORM_2) *wlte = PetscSqrtReal(PetscSqr(enormX) / 2 + PetscSqr(enormV) / 2);
    349:   else *wlte = PetscMax(enormX, enormV);
    350:   if (order) *order = 2;
    351:   PetscFunctionReturn(PETSC_SUCCESS);
    352: }

    354: static PetscErrorCode TSRollBack_Alpha(TS ts)
    355: {
    356:   TS_Alpha *th = (TS_Alpha *)ts->data;

    358:   PetscFunctionBegin;
    359:   PetscCall(VecCopy(th->X0, ts->vec_sol));
    360:   PetscCall(VecCopy(th->V0, ts->vec_dot));
    361:   PetscFunctionReturn(PETSC_SUCCESS);
    362: }

    364: /*
    365: static PetscErrorCode TSInterpolate_Alpha(TS ts,PetscReal t,Vec X,Vec V)
    366: {
    367:   TS_Alpha       *th = (TS_Alpha*)ts->data;
    368:   PetscReal      dt  = t - ts->ptime;

    370:   PetscFunctionBegin;
    371:   PetscCall(VecCopy(ts->vec_dot,V));
    372:   PetscCall(VecAXPY(V,dt*(1-th->Gamma),th->A0));
    373:   PetscCall(VecAXPY(V,dt*th->Gamma,th->A1));
    374:   PetscCall(VecCopy(ts->vec_sol,X));
    375:   PetscCall(VecAXPY(X,dt,V));
    376:   PetscCall(VecAXPY(X,dt*dt*((PetscReal)0.5-th->Beta),th->A0));
    377:   PetscCall(VecAXPY(X,dt*dt*th->Beta,th->A1));
    378:   PetscFunctionReturn(PETSC_SUCCESS);
    379: }
    380: */

    382: static PetscErrorCode SNESTSFormFunction_Alpha(PETSC_UNUSED SNES snes, Vec X, Vec F, TS ts)
    383: {
    384:   TS_Alpha *th = (TS_Alpha *)ts->data;
    385:   PetscReal ta = th->stage_time;
    386:   Vec       Xa = th->Xa, Va = th->Va, Aa = th->Aa;

    388:   PetscFunctionBegin;
    389:   PetscCall(TSAlpha_StageVecs(ts, X));
    390:   /* F = Function(ta,Xa,Va,Aa) */
    391:   PetscCall(TSComputeI2Function(ts, ta, Xa, Va, Aa, F));
    392:   PetscCall(VecScale(F, th->scale_F));
    393:   PetscFunctionReturn(PETSC_SUCCESS);
    394: }

    396: static PetscErrorCode SNESTSFormJacobian_Alpha(PETSC_UNUSED SNES snes, PETSC_UNUSED Vec X, Mat J, Mat P, TS ts)
    397: {
    398:   TS_Alpha *th = (TS_Alpha *)ts->data;
    399:   PetscReal ta = th->stage_time;
    400:   Vec       Xa = th->Xa, Va = th->Va, Aa = th->Aa;
    401:   PetscReal dVdX = th->shift_V, dAdX = th->shift_A;

    403:   PetscFunctionBegin;
    404:   /* J,P = Jacobian(ta,Xa,Va,Aa) */
    405:   PetscCall(TSComputeI2Jacobian(ts, ta, Xa, Va, Aa, dVdX, dAdX, J, P));
    406:   PetscFunctionReturn(PETSC_SUCCESS);
    407: }

    409: static PetscErrorCode TSReset_Alpha(TS ts)
    410: {
    411:   TS_Alpha *th = (TS_Alpha *)ts->data;

    413:   PetscFunctionBegin;
    414:   PetscCall(VecDestroy(&th->X0));
    415:   PetscCall(VecDestroy(&th->Xa));
    416:   PetscCall(VecDestroy(&th->X1));
    417:   PetscCall(VecDestroy(&th->V0));
    418:   PetscCall(VecDestroy(&th->Va));
    419:   PetscCall(VecDestroy(&th->V1));
    420:   PetscCall(VecDestroy(&th->A0));
    421:   PetscCall(VecDestroy(&th->Aa));
    422:   PetscCall(VecDestroy(&th->A1));
    423:   PetscCall(VecDestroy(&th->vec_sol_prev));
    424:   PetscCall(VecDestroy(&th->vec_dot_prev));
    425:   PetscCall(VecDestroy(&th->vec_lte_work[0]));
    426:   PetscCall(VecDestroy(&th->vec_lte_work[1]));
    427:   PetscFunctionReturn(PETSC_SUCCESS);
    428: }

    430: static PetscErrorCode TSDestroy_Alpha(TS ts)
    431: {
    432:   PetscFunctionBegin;
    433:   PetscCall(TSReset_Alpha(ts));
    434:   PetscCall(PetscFree(ts->data));

    436:   PetscCall(PetscObjectComposeFunction((PetscObject)ts, "TSAlpha2SetRadius_C", NULL));
    437:   PetscCall(PetscObjectComposeFunction((PetscObject)ts, "TSAlpha2SetParams_C", NULL));
    438:   PetscCall(PetscObjectComposeFunction((PetscObject)ts, "TSAlpha2GetParams_C", NULL));
    439:   PetscFunctionReturn(PETSC_SUCCESS);
    440: }

    442: static PetscErrorCode TSSetUp_Alpha(TS ts)
    443: {
    444:   TS_Alpha *th = (TS_Alpha *)ts->data;
    445:   PetscBool match;

    447:   PetscFunctionBegin;
    448:   PetscCall(VecDuplicate(ts->vec_sol, &th->X0));
    449:   PetscCall(VecDuplicate(ts->vec_sol, &th->Xa));
    450:   PetscCall(VecDuplicate(ts->vec_sol, &th->X1));
    451:   PetscCall(VecDuplicate(ts->vec_sol, &th->V0));
    452:   PetscCall(VecDuplicate(ts->vec_sol, &th->Va));
    453:   PetscCall(VecDuplicate(ts->vec_sol, &th->V1));
    454:   PetscCall(VecDuplicate(ts->vec_sol, &th->A0));
    455:   PetscCall(VecDuplicate(ts->vec_sol, &th->Aa));
    456:   PetscCall(VecDuplicate(ts->vec_sol, &th->A1));

    458:   PetscCall(TSGetAdapt(ts, &ts->adapt));
    459:   PetscCall(TSAdaptCandidatesClear(ts->adapt));
    460:   PetscCall(PetscObjectTypeCompare((PetscObject)ts->adapt, TSADAPTNONE, &match));
    461:   if (!match) {
    462:     PetscCall(VecDuplicate(ts->vec_sol, &th->vec_sol_prev));
    463:     PetscCall(VecDuplicate(ts->vec_sol, &th->vec_dot_prev));
    464:     PetscCall(VecDuplicate(ts->vec_sol, &th->vec_lte_work[0]));
    465:     PetscCall(VecDuplicate(ts->vec_sol, &th->vec_lte_work[1]));
    466:   }

    468:   PetscCall(TSGetSNES(ts, &ts->snes));
    469:   PetscFunctionReturn(PETSC_SUCCESS);
    470: }

    472: static PetscErrorCode TSSetFromOptions_Alpha(TS ts, PetscOptionItems PetscOptionsObject)
    473: {
    474:   TS_Alpha *th = (TS_Alpha *)ts->data;

    476:   PetscFunctionBegin;
    477:   PetscOptionsHeadBegin(PetscOptionsObject, "Generalized-Alpha ODE solver options");
    478:   {
    479:     PetscBool flg;
    480:     PetscReal radius = 1;
    481:     PetscCall(PetscOptionsReal("-ts_alpha_radius", "Spectral radius (high-frequency dissipation)", "TSAlpha2SetRadius", radius, &radius, &flg));
    482:     if (flg) PetscCall(TSAlpha2SetRadius(ts, radius));
    483:     PetscCall(PetscOptionsReal("-ts_alpha_alpha_m", "Algorithmic parameter alpha_m", "TSAlpha2SetParams", th->Alpha_m, &th->Alpha_m, NULL));
    484:     PetscCall(PetscOptionsReal("-ts_alpha_alpha_f", "Algorithmic parameter alpha_f", "TSAlpha2SetParams", th->Alpha_f, &th->Alpha_f, NULL));
    485:     PetscCall(PetscOptionsReal("-ts_alpha_gamma", "Algorithmic parameter gamma", "TSAlpha2SetParams", th->Gamma, &th->Gamma, NULL));
    486:     PetscCall(PetscOptionsReal("-ts_alpha_beta", "Algorithmic parameter beta", "TSAlpha2SetParams", th->Beta, &th->Beta, NULL));
    487:     PetscCall(TSAlpha2SetParams(ts, th->Alpha_m, th->Alpha_f, th->Gamma, th->Beta));
    488:   }
    489:   PetscOptionsHeadEnd();
    490:   PetscFunctionReturn(PETSC_SUCCESS);
    491: }

    493: static PetscErrorCode TSView_Alpha(TS ts, PetscViewer viewer)
    494: {
    495:   TS_Alpha *th = (TS_Alpha *)ts->data;
    496:   PetscBool iascii;

    498:   PetscFunctionBegin;
    499:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &iascii));
    500:   if (iascii) PetscCall(PetscViewerASCIIPrintf(viewer, "  Alpha_m=%g, Alpha_f=%g, Gamma=%g, Beta=%g\n", (double)th->Alpha_m, (double)th->Alpha_f, (double)th->Gamma, (double)th->Beta));
    501:   PetscFunctionReturn(PETSC_SUCCESS);
    502: }

    504: static PetscErrorCode TSAlpha2SetRadius_Alpha(TS ts, PetscReal radius)
    505: {
    506:   PetscReal alpha_m, alpha_f, gamma, beta;

    508:   PetscFunctionBegin;
    509:   PetscCheck(radius >= 0 && radius <= 1, PetscObjectComm((PetscObject)ts), PETSC_ERR_ARG_OUTOFRANGE, "Radius %g not in range [0,1]", (double)radius);
    510:   alpha_m = (2 - radius) / (1 + radius);
    511:   alpha_f = 1 / (1 + radius);
    512:   gamma   = (PetscReal)0.5 + alpha_m - alpha_f;
    513:   beta    = (PetscReal)0.5 * (1 + alpha_m - alpha_f);
    514:   beta *= beta;
    515:   PetscCall(TSAlpha2SetParams(ts, alpha_m, alpha_f, gamma, beta));
    516:   PetscFunctionReturn(PETSC_SUCCESS);
    517: }

    519: static PetscErrorCode TSAlpha2SetParams_Alpha(TS ts, PetscReal alpha_m, PetscReal alpha_f, PetscReal gamma, PetscReal beta)
    520: {
    521:   TS_Alpha *th  = (TS_Alpha *)ts->data;
    522:   PetscReal tol = 100 * PETSC_MACHINE_EPSILON;
    523:   PetscReal res = ((PetscReal)0.5 + alpha_m - alpha_f) - gamma;

    525:   PetscFunctionBegin;
    526:   th->Alpha_m = alpha_m;
    527:   th->Alpha_f = alpha_f;
    528:   th->Gamma   = gamma;
    529:   th->Beta    = beta;
    530:   th->order   = (PetscAbsReal(res) < tol) ? 2 : 1;
    531:   PetscFunctionReturn(PETSC_SUCCESS);
    532: }

    534: static PetscErrorCode TSAlpha2GetParams_Alpha(TS ts, PetscReal *alpha_m, PetscReal *alpha_f, PetscReal *gamma, PetscReal *beta)
    535: {
    536:   TS_Alpha *th = (TS_Alpha *)ts->data;

    538:   PetscFunctionBegin;
    539:   if (alpha_m) *alpha_m = th->Alpha_m;
    540:   if (alpha_f) *alpha_f = th->Alpha_f;
    541:   if (gamma) *gamma = th->Gamma;
    542:   if (beta) *beta = th->Beta;
    543:   PetscFunctionReturn(PETSC_SUCCESS);
    544: }

    546: /*MC
    547:   TSALPHA2 - ODE/DAE solver using the implicit Generalized-Alpha method for second-order systems {cite}`chung1993`

    549:   Level: beginner

    551: .seealso: [](ch_ts), `TS`, `TSCreate()`, `TSSetType()`, `TSAlpha2SetRadius()`, `TSAlpha2SetParams()`
    552: M*/
    553: PETSC_EXTERN PetscErrorCode TSCreate_Alpha2(TS ts)
    554: {
    555:   TS_Alpha *th;

    557:   PetscFunctionBegin;
    558:   ts->ops->reset          = TSReset_Alpha;
    559:   ts->ops->destroy        = TSDestroy_Alpha;
    560:   ts->ops->view           = TSView_Alpha;
    561:   ts->ops->setup          = TSSetUp_Alpha;
    562:   ts->ops->setfromoptions = TSSetFromOptions_Alpha;
    563:   ts->ops->step           = TSStep_Alpha;
    564:   ts->ops->evaluatewlte   = TSEvaluateWLTE_Alpha;
    565:   ts->ops->rollback       = TSRollBack_Alpha;
    566:   /*ts->ops->interpolate  = TSInterpolate_Alpha;*/
    567:   ts->ops->snesfunction  = SNESTSFormFunction_Alpha;
    568:   ts->ops->snesjacobian  = SNESTSFormJacobian_Alpha;
    569:   ts->default_adapt_type = TSADAPTNONE;

    571:   ts->usessnes = PETSC_TRUE;

    573:   PetscCall(PetscNew(&th));
    574:   ts->data = (void *)th;

    576:   th->Alpha_m = 0.5;
    577:   th->Alpha_f = 0.5;
    578:   th->Gamma   = 0.5;
    579:   th->Beta    = 0.25;
    580:   th->order   = 2;

    582:   th->predictor     = NULL;
    583:   th->predictor_ctx = NULL;

    585:   PetscCall(PetscObjectComposeFunction((PetscObject)ts, "TSAlpha2SetRadius_C", TSAlpha2SetRadius_Alpha));
    586:   PetscCall(PetscObjectComposeFunction((PetscObject)ts, "TSAlpha2SetParams_C", TSAlpha2SetParams_Alpha));
    587:   PetscCall(PetscObjectComposeFunction((PetscObject)ts, "TSAlpha2GetParams_C", TSAlpha2GetParams_Alpha));
    588:   PetscFunctionReturn(PETSC_SUCCESS);
    589: }

    591: /*@
    592:   TSAlpha2SetRadius - sets the desired spectral radius of the method for `TSALPHA2`
    593:   (i.e. high-frequency numerical damping)

    595:   Logically Collective

    597:   Input Parameters:
    598: + ts     - timestepping context
    599: - radius - the desired spectral radius

    601:   Options Database Key:
    602: . -ts_alpha_radius <radius> - set the desired spectral radius

    604:   Level: intermediate

    606:   Notes:

    608:   The algorithmic parameters $\alpha_m$ and $\alpha_f$ of the generalized-$\alpha$ method can
    609:   be computed in terms of a specified spectral radius $\rho$ in `[0, 1]` for infinite time step
    610:   in order to control high-frequency numerical damping\:

    612:   $$
    613:   \begin{align*}
    614:   \alpha_m = (2-\rho)/(1+\rho) \\
    615:   \alpha_f = 1/(1+\rho)
    616:   \end{align*}
    617:   $$

    619: .seealso: [](ch_ts), `TS`, `TSALPHA2`, `TSAlpha2SetParams()`, `TSAlpha2GetParams()`
    620: @*/
    621: PetscErrorCode TSAlpha2SetRadius(TS ts, PetscReal radius)
    622: {
    623:   PetscFunctionBegin;
    626:   PetscCheck(radius >= 0 && radius <= 1, ((PetscObject)ts)->comm, PETSC_ERR_ARG_OUTOFRANGE, "Radius %g not in range [0,1]", (double)radius);
    627:   PetscTryMethod(ts, "TSAlpha2SetRadius_C", (TS, PetscReal), (ts, radius));
    628:   PetscFunctionReturn(PETSC_SUCCESS);
    629: }

    631: /*@
    632:   TSAlpha2SetParams - sets the algorithmic parameters for `TSALPHA2`

    634:   Logically Collective

    636:   Input Parameters:
    637: + ts      - timestepping context
    638: . alpha_m - algorithmic parameter
    639: . alpha_f - algorithmic parameter
    640: . gamma   - algorithmic parameter
    641: - beta    - algorithmic parameter

    643:   Options Database Keys:
    644: + -ts_alpha_alpha_m <alpha_m> - set alpha_m
    645: . -ts_alpha_alpha_f <alpha_f> - set alpha_f
    646: . -ts_alpha_gamma   <gamma>   - set gamma
    647: - -ts_alpha_beta    <beta>    - set beta

    649:   Level: advanced

    651:   Notes:
    652:   Second-order accuracy can be obtained so long as\:

    654:   $$
    655:   \begin{align*}
    656:   \gamma = 1/2 + \alpha_m - \alpha_f \\
    657:   \beta  = 1/4 (1 + \alpha_m - \alpha_f)^2.
    658:   \end{align*}
    659:   $$

    661:   Unconditional stability requires\:
    662:   $$
    663:   \alpha_m >= \alpha_f >= 1/2.
    664:   $$

    666:   Use of this function is normally only required to hack `TSALPHA2` to use a modified
    667:   integration scheme. Users should call `TSAlpha2SetRadius()` to set the desired spectral
    668:   radius of the methods (i.e. high-frequency damping) in order so select optimal values for
    669:   these parameters.

    671: .seealso: [](ch_ts), `TS`, `TSALPHA2`, `TSAlpha2SetRadius()`, `TSAlpha2GetParams()`
    672: @*/
    673: PetscErrorCode TSAlpha2SetParams(TS ts, PetscReal alpha_m, PetscReal alpha_f, PetscReal gamma, PetscReal beta)
    674: {
    675:   PetscFunctionBegin;
    681:   PetscTryMethod(ts, "TSAlpha2SetParams_C", (TS, PetscReal, PetscReal, PetscReal, PetscReal), (ts, alpha_m, alpha_f, gamma, beta));
    682:   PetscFunctionReturn(PETSC_SUCCESS);
    683: }

    685: /*@
    686:   TSAlpha2GetParams - gets the algorithmic parameters for `TSALPHA2`

    688:   Not Collective

    690:   Input Parameter:
    691: . ts - timestepping context

    693:   Output Parameters:
    694: + alpha_m - algorithmic parameter
    695: . alpha_f - algorithmic parameter
    696: . gamma   - algorithmic parameter
    697: - beta    - algorithmic parameter

    699:   Level: advanced

    701:   Note:
    702:   Use of this function is normally only required to hack `TSALPHA2` to use a modified
    703:   integration scheme. Users should call `TSAlpha2SetRadius()` to set the high-frequency damping
    704:   (i.e. spectral radius of the method) in order so select optimal values for these parameters.

    706: .seealso: [](ch_ts), `TS`, `TSALPHA2`, `TSAlpha2SetRadius()`, `TSAlpha2SetParams()`
    707: @*/
    708: PetscErrorCode TSAlpha2GetParams(TS ts, PetscReal *alpha_m, PetscReal *alpha_f, PetscReal *gamma, PetscReal *beta)
    709: {
    710:   PetscFunctionBegin;
    712:   if (alpha_m) PetscAssertPointer(alpha_m, 2);
    713:   if (alpha_f) PetscAssertPointer(alpha_f, 3);
    714:   if (gamma) PetscAssertPointer(gamma, 4);
    715:   if (beta) PetscAssertPointer(beta, 5);
    716:   PetscUseMethod(ts, "TSAlpha2GetParams_C", (TS, PetscReal *, PetscReal *, PetscReal *, PetscReal *), (ts, alpha_m, alpha_f, gamma, beta));
    717:   PetscFunctionReturn(PETSC_SUCCESS);
    718: }