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AdvectiveFluxCalculatorBase.C
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9 
11 #include "Conversion.h" // for stringify
12 
13 #include "libmesh/string_to_enum.h"
14 #include "libmesh/mesh_tools.h"
15 #include "libmesh/parallel_sync.h"
16 
19 {
21  params.addClassDescription(
22  "Base class to compute K_ij (a measure of advective flux from node i to node j) "
23  "and R+ and R- (which quantify amount of antidiffusion to add) in the "
24  "Kuzmin-Turek FEM-TVD multidimensional scheme");
25  MooseEnum flux_limiter_type("MinMod VanLeer MC superbee None", "VanLeer");
26  params.addParam<MooseEnum>("flux_limiter_type",
27  flux_limiter_type,
28  "Type of flux limiter to use. 'None' means that no antidiffusion "
29  "will be added in the Kuzmin-Turek scheme");
30  params.addRangeCheckedParam<Real>(
31  "allowable_MB_wastage",
32  5.0,
33  "allowable_MB_wastage > 0.0",
34  "This object will issue a memory warning if the internal node-numbering data structure "
35  "wastes more than allowable_MB_wastage megabytes. This data structure uses sequential "
36  "node-numbering which is optimized for speed rather than memory efficiency");
37 
38  params.addRelationshipManager("ElementPointNeighborLayers",
42  [](const InputParameters &, InputParameters & rm_params)
43  { rm_params.set<unsigned short>("layers") = 2; });
44 
45  params.set<ExecFlagEnum>("execute_on", true) = {EXEC_LINEAR};
46  return params;
47 }
48 
50  : ElementUserObject(parameters),
51  _resizing_needed(true),
52  _flux_limiter_type(getParam<MooseEnum>("flux_limiter_type").getEnum<FluxLimiterTypeEnum>()),
53  _kij(),
54  _flux_out(),
55  _dflux_out_du(),
56  _dflux_out_dKjk(),
57  _valence(),
58  _u_nodal(),
59  _u_nodal_computed_by_thread(),
60  _connections(),
61  _number_of_nodes(0),
62  _my_pid(processor_id()),
63  _nodes_to_receive(),
64  _nodes_to_send(),
65  _pairs_to_receive(),
66  _pairs_to_send(),
67  _allowable_MB_wastage(getParam<Real>("allowable_MB_wastage"))
68 {
70  paramError(
71  "execute_on",
72  "The AdvectiveFluxCalculator UserObject " + name() +
73  " execute_on parameter must include, at least, 'linear'. This is to ensure that "
74  "this UserObject computes all necessary quantities just before the Kernels evaluate "
75  "their Residuals");
76 }
77 
78 void
80 {
81  // If needed, size and initialize quantities appropriately, and compute _valence
82  if (_resizing_needed)
83  {
84  /*
85  * Populate _connections for all nodes that can be seen by this processor and on relevant
86  * blocks
87  *
88  * MULTIPROC NOTE: this must loop over local elements and 2 layers of ghosted elements.
89  * The Kernel will only loop over local elements, so will only use _kij, etc, for
90  * linked node-node pairs that appear in the local elements. Nevertheless, we
91  * need to build _kij, etc, for the nodes in the ghosted elements in order to simplify
92  * Jacobian computations
93  */
95  for (const auto & elem : _fe_problem.getNonlinearEvaluableElementRange())
96  if (this->hasBlocks(elem->subdomain_id()))
97  for (unsigned i = 0; i < elem->n_nodes(); ++i)
98  _connections.addGlobalNode(elem->node_id(i));
100  for (const auto & elem : _fe_problem.getNonlinearEvaluableElementRange())
101  if (this->hasBlocks(elem->subdomain_id()))
102  for (unsigned i = 0; i < elem->n_nodes(); ++i)
103  for (unsigned j = 0; j < elem->n_nodes(); ++j)
104  _connections.addConnection(elem->node_id(i), elem->node_id(j));
106 
108 
109  Real mb_wasted = (_connections.sizeSequential() - _number_of_nodes) * 4.0 / 1048576;
110  gatherMax(mb_wasted);
111  if (mb_wasted > _allowable_MB_wastage)
112  mooseWarning(
113  "In at least one processor, the sequential node-numbering internal data structure used "
114  "in " +
115  name() + " is using memory inefficiently.\nThe memory wasted is " +
116  Moose::stringify(mb_wasted) +
117  " megabytes.\n The node-numbering data structure has been optimized for speed at the "
118  "expense of memory, but that may not be an appropriate optimization for your case, "
119  "because the node numbering is not close to sequential in your case.\n");
120 
121  // initialize _kij
122  _kij.resize(_number_of_nodes);
123  for (dof_id_type sequential_i = 0; sequential_i < _number_of_nodes; ++sequential_i)
124  _kij[sequential_i].assign(
125  _connections.sequentialConnectionsToSequentialID(sequential_i).size(), 0.0);
126 
127  /*
128  * Build _valence[i], which is the number of times the sequential node i is encountered when
129  * looping over the entire mesh (and on relevant blocks)
130  *
131  * MULTIPROC NOTE: this must loop over local elements and >=1 layer of ghosted elements.
132  * The Kernel will only loop over local elements, so will only use _valence for
133  * linked node-node pairs that appear in the local elements. But other processors will
134  * loop over neighboring elements, so avoid multiple counting of the residual and Jacobian
135  * this processor must record how many times each node-node link of its local elements
136  * appears in the local elements and >=1 layer, and pass that info to the Kernel
137  */
138  _valence.assign(_number_of_nodes, 0);
139  for (const auto & elem : _fe_problem.getNonlinearEvaluableElementRange())
140  if (this->hasBlocks(elem->subdomain_id()))
141  for (unsigned i = 0; i < elem->n_nodes(); ++i)
142  {
143  const dof_id_type node_i = elem->node_id(i);
144  const dof_id_type sequential_i = _connections.sequentialID(node_i);
145  _valence[sequential_i] += 1;
146  }
147 
148  _u_nodal.assign(_number_of_nodes, 0.0);
150  _flux_out.assign(_number_of_nodes, 0.0);
151  _dflux_out_du.assign(_number_of_nodes, std::map<dof_id_type, Real>());
152  for (dof_id_type sequential_i = 0; sequential_i < _number_of_nodes; ++sequential_i)
153  zeroedConnection(_dflux_out_du[sequential_i], _connections.globalID(sequential_i));
155  for (dof_id_type sequential_i = 0; sequential_i < _number_of_nodes; ++sequential_i)
156  {
157  const std::vector<dof_id_type> con_i =
159  const std::size_t num_con_i = con_i.size();
160  _dflux_out_dKjk[sequential_i].resize(num_con_i);
161  for (std::size_t j = 0; j < con_i.size(); ++j)
162  {
163  const dof_id_type sequential_j = con_i[j];
164  const std::size_t num_con_j =
166  _dflux_out_dKjk[sequential_i][j].assign(num_con_j, 0.0);
167  }
168  }
169 
170  if (_app.n_processors() > 1)
171  buildCommLists();
172 
173  _resizing_needed = false;
174 
175  // Clear and size all member vectors
176  _dij.assign(_number_of_nodes, {});
177  _dDij_dKij.assign(_number_of_nodes, {});
178  _dDij_dKji.assign(_number_of_nodes, {});
179  _dDii_dKij.assign(_number_of_nodes, {});
180  _dDii_dKji.assign(_number_of_nodes, {});
181  _lij.assign(_number_of_nodes, {});
182  _rP.assign(_number_of_nodes, 0.0);
183  _rM.assign(_number_of_nodes, 0.0);
184  _drP.assign(_number_of_nodes, {});
185  _drM.assign(_number_of_nodes, {});
186  _drP_dk.assign(_number_of_nodes, {});
187  _drM_dk.assign(_number_of_nodes, {});
188  _fa.assign(_number_of_nodes, {});
189  _dfa.assign(_number_of_nodes, {});
190  _dFij_dKik.assign(_number_of_nodes, {});
191  _dFij_dKjk.assign(_number_of_nodes, {});
192  }
193 }
194 
195 void
197 {
199 
200  // Signal that _kij, _valence, etc need to be rebuilt
201  _resizing_needed = true;
202 }
203 
204 void
206 {
207  // Zero _kij and falsify _u_nodal_computed_by_thread ready for building in execute() and
208  // finalize()
210  for (dof_id_type sequential_i = 0; sequential_i < _number_of_nodes; ++sequential_i)
211  _kij[sequential_i].assign(_connections.sequentialConnectionsToSequentialID(sequential_i).size(),
212  0.0);
213 }
214 
215 void
217 {
218  // compute _kij contributions from this element that is local to this processor
219  // and record _u_nodal
220  for (unsigned i = 0; i < _current_elem->n_nodes(); ++i)
221  {
222  const dof_id_type node_i = _current_elem->node_id(i);
223  const dof_id_type sequential_i = _connections.sequentialID(node_i);
224  if (!_u_nodal_computed_by_thread[sequential_i])
225  {
226  _u_nodal[sequential_i] = computeU(i);
227  _u_nodal_computed_by_thread[sequential_i] = true;
228  }
229  for (unsigned j = 0; j < _current_elem->n_nodes(); ++j)
230  {
231  const dof_id_type node_j = _current_elem->node_id(j);
232  for (unsigned qp = 0; qp < _qrule->n_points(); ++qp)
233  executeOnElement(node_i, node_j, i, j, qp);
234  }
235  }
236 }
237 
238 void
240  dof_id_type global_i, dof_id_type global_j, unsigned local_i, unsigned local_j, unsigned qp)
241 {
242  // KT Eqn (20)
243  const dof_id_type sequential_i = _connections.sequentialID(global_i);
244  const unsigned index_i_to_j = _connections.indexOfGlobalConnection(global_i, global_j);
245  _kij[sequential_i][index_i_to_j] += _JxW[qp] * _coord[qp] * computeVelocity(local_i, local_j, qp);
246 }
247 
248 void
250 {
251  const auto & afc = static_cast<const AdvectiveFluxCalculatorBase &>(uo);
252  // add the values of _kij computed by different threads
253  for (dof_id_type sequential_i = 0; sequential_i < _number_of_nodes; ++sequential_i)
254  {
255  const std::size_t num_con_i =
257  for (std::size_t j = 0; j < num_con_i; ++j)
258  _kij[sequential_i][j] += afc._kij[sequential_i][j];
259  }
260 
261  // gather the values of _u_nodal computed by different threads
262  for (dof_id_type sequential_i = 0; sequential_i < _number_of_nodes; ++sequential_i)
263  if (!_u_nodal_computed_by_thread[sequential_i] && afc._u_nodal_computed_by_thread[sequential_i])
264  _u_nodal[sequential_i] = afc._u_nodal[sequential_i];
265 }
266 
267 void
269 {
270  // Overall: ensure _kij is fully built, then compute Kuzmin-Turek D, L, f^a and
271  // relevant Jacobian information, and then the relevant quantities into _flux_out and
272  // _dflux_out_du, _dflux_out_dKjk
273 
274  if (_app.n_processors() > 1)
276 
277  // Calculate KuzminTurek D matrix
278  // See Eqn (32)
279  // This adds artificial diffusion, which eliminates any spurious oscillations
280  // The idea is that D will remove all negative off-diagonal elements when it is added to K
281  // This is identical to full upwinding
282  for (dof_id_type sequential_i = 0; sequential_i < _number_of_nodes; ++sequential_i)
283  {
284  const std::vector<dof_id_type> & con_i =
286  const std::size_t num_con_i = con_i.size();
287  _dij[sequential_i].assign(num_con_i, 0.0);
288  _dDij_dKij[sequential_i].assign(num_con_i, 0.0);
289  _dDij_dKji[sequential_i].assign(num_con_i, 0.0);
290  _dDii_dKij[sequential_i].assign(num_con_i, 0.0);
291  _dDii_dKji[sequential_i].assign(num_con_i, 0.0);
292  const unsigned index_i_to_i =
293  _connections.indexOfSequentialConnection(sequential_i, sequential_i);
294  for (std::size_t j = 0; j < num_con_i; ++j)
295  {
296  const dof_id_type sequential_j = con_i[j];
297  if (sequential_i == sequential_j)
298  continue;
299  const unsigned index_j_to_i =
300  _connections.indexOfSequentialConnection(sequential_j, sequential_i);
301  const Real kij = _kij[sequential_i][j];
302  const Real kji = _kij[sequential_j][index_j_to_i];
303  if ((kij <= kji) && (kij < 0.0))
304  {
305  _dij[sequential_i][j] = -kij;
306  _dDij_dKij[sequential_i][j] = -1.0;
307  _dDii_dKij[sequential_i][j] += 1.0;
308  }
309  else if ((kji <= kij) && (kji < 0.0))
310  {
311  _dij[sequential_i][j] = -kji;
312  _dDij_dKji[sequential_i][j] = -1.0;
313  _dDii_dKji[sequential_i][j] += 1.0;
314  }
315  else
316  _dij[sequential_i][j] = 0.0;
317  _dij[sequential_i][index_i_to_i] -= _dij[sequential_i][j];
318  }
319  }
320 
321  // Calculate KuzminTurek L matrix
322  // See Fig 2: L = K + D
323  for (dof_id_type sequential_i = 0; sequential_i < _number_of_nodes; ++sequential_i)
324  {
325  const std::vector<dof_id_type> & con_i =
327  const std::size_t num_con_i = con_i.size();
328  _lij[sequential_i].assign(num_con_i, 0.0);
329  for (std::size_t j = 0; j < num_con_i; ++j)
330  _lij[sequential_i][j] = _kij[sequential_i][j] + _dij[sequential_i][j];
331  }
332 
333  // Compute KuzminTurek R matrices
334  // See Eqns (49) and (12)
335  for (dof_id_type sequential_i = 0; sequential_i < _number_of_nodes; ++sequential_i)
336  {
337  _rP[sequential_i] = rPlus(sequential_i, _drP[sequential_i], _drP_dk[sequential_i]);
338  _rM[sequential_i] = rMinus(sequential_i, _drM[sequential_i], _drM_dk[sequential_i]);
339  }
340 
341  // Calculate KuzminTurek f^{a} matrix
342  // This is the antidiffusive flux
343  // See Eqn (50)
344  for (dof_id_type sequential_i = 0; sequential_i < _number_of_nodes; ++sequential_i)
345  {
346  const std::vector<dof_id_type> & con_i =
348  const unsigned num_con_i = con_i.size();
349  _fa[sequential_i].assign(num_con_i, 0.0);
350  _dfa[sequential_i].resize(num_con_i);
351  _dFij_dKik[sequential_i].resize(num_con_i);
352  _dFij_dKjk[sequential_i].resize(num_con_i);
353  for (std::size_t j = 0; j < num_con_i; ++j)
354  {
355  for (const auto & global_k : con_i)
356  _dfa[sequential_i][j][global_k] = 0;
357  const dof_id_type global_j = con_i[j];
358  const std::vector<dof_id_type> & con_j = _connections.globalConnectionsToGlobalID(global_j);
359  const unsigned num_con_j = con_j.size();
360  for (const auto & global_k : con_j)
361  _dfa[sequential_i][j][global_k] = 0;
362  _dFij_dKik[sequential_i][j].assign(num_con_i, 0.0);
363  _dFij_dKjk[sequential_i][j].assign(num_con_j, 0.0);
364  }
365  }
366 
367  for (dof_id_type sequential_i = 0; sequential_i < _number_of_nodes; ++sequential_i)
368  {
369  const dof_id_type global_i = _connections.globalID(sequential_i);
370  const Real u_i = _u_nodal[sequential_i];
371  const std::vector<dof_id_type> & con_i =
373  const std::size_t num_con_i = con_i.size();
374  for (std::size_t j = 0; j < num_con_i; ++j)
375  {
376  const dof_id_type sequential_j = con_i[j];
377  if (sequential_i == sequential_j)
378  continue;
379  const unsigned index_j_to_i =
380  _connections.indexOfSequentialConnection(sequential_j, sequential_i);
381  const Real Lij = _lij[sequential_i][j];
382  const Real Lji = _lij[sequential_j][index_j_to_i];
383  if (Lji >= Lij) // node i is upwind of node j.
384  {
385  const Real Dij = _dij[sequential_i][j];
386  const dof_id_type global_j = _connections.globalID(sequential_j);
387  const Real u_j = _u_nodal[sequential_j];
388  Real prefactor = 0.0;
389  std::vector<Real> dprefactor_du(num_con_i,
390  0.0); // dprefactor_du[j] = d(prefactor)/du[sequential_j]
391  std::vector<Real> dprefactor_dKij(
392  num_con_i, 0.0); // dprefactor_dKij[j] = d(prefactor)/dKij[sequential_i][j].
393  Real dprefactor_dKji = 0; // dprefactor_dKji = d(prefactor)/dKij[sequential_j][index_j_to_i]
394  if (u_i >= u_j)
395  {
396  if (Lji <= _rP[sequential_i] * Dij)
397  {
398  prefactor = Lji;
399  dprefactor_dKij[j] += _dDij_dKji[sequential_j][index_j_to_i];
400  dprefactor_dKji += 1.0 + _dDij_dKij[sequential_j][index_j_to_i];
401  }
402  else
403  {
404  prefactor = _rP[sequential_i] * Dij;
405  for (std::size_t ind_j = 0; ind_j < num_con_i; ++ind_j)
406  dprefactor_du[ind_j] = _drP[sequential_i][ind_j] * Dij;
407  dprefactor_dKij[j] += _rP[sequential_i] * _dDij_dKij[sequential_i][j];
408  dprefactor_dKji += _rP[sequential_i] * _dDij_dKji[sequential_i][j];
409  for (std::size_t ind_j = 0; ind_j < num_con_i; ++ind_j)
410  dprefactor_dKij[ind_j] += _drP_dk[sequential_i][ind_j] * Dij;
411  }
412  }
413  else
414  {
415  if (Lji <= _rM[sequential_i] * Dij)
416  {
417  prefactor = Lji;
418  dprefactor_dKij[j] += _dDij_dKji[sequential_j][index_j_to_i];
419  dprefactor_dKji += 1.0 + _dDij_dKij[sequential_j][index_j_to_i];
420  }
421  else
422  {
423  prefactor = _rM[sequential_i] * Dij;
424  for (std::size_t ind_j = 0; ind_j < num_con_i; ++ind_j)
425  dprefactor_du[ind_j] = _drM[sequential_i][ind_j] * Dij;
426  dprefactor_dKij[j] += _rM[sequential_i] * _dDij_dKij[sequential_i][j];
427  dprefactor_dKji += _rM[sequential_i] * _dDij_dKji[sequential_i][j];
428  for (std::size_t ind_j = 0; ind_j < num_con_i; ++ind_j)
429  dprefactor_dKij[ind_j] += _drM_dk[sequential_i][ind_j] * Dij;
430  }
431  }
432  _fa[sequential_i][j] = prefactor * (u_i - u_j);
433  _dfa[sequential_i][j][global_i] = prefactor;
434  _dfa[sequential_i][j][global_j] = -prefactor;
435  for (std::size_t ind_j = 0; ind_j < num_con_i; ++ind_j)
436  {
437  _dfa[sequential_i][j][_connections.globalID(con_i[ind_j])] +=
438  dprefactor_du[ind_j] * (u_i - u_j);
439  _dFij_dKik[sequential_i][j][ind_j] += dprefactor_dKij[ind_j] * (u_i - u_j);
440  }
441  _dFij_dKjk[sequential_i][j][index_j_to_i] += dprefactor_dKji * (u_i - u_j);
442  }
443  }
444  }
445 
446  for (dof_id_type sequential_i = 0; sequential_i < _number_of_nodes; ++sequential_i)
447  {
448  const std::vector<dof_id_type> & con_i =
450  const std::size_t num_con_i = con_i.size();
451  for (std::size_t j = 0; j < num_con_i; ++j)
452  {
453  const dof_id_type sequential_j = con_i[j];
454  if (sequential_i == sequential_j)
455  continue;
456  const unsigned index_j_to_i =
457  _connections.indexOfSequentialConnection(sequential_j, sequential_i);
458  if (_lij[sequential_j][index_j_to_i] < _lij[sequential_i][j]) // node_i is downwind of node_j.
459  {
460  _fa[sequential_i][j] = -_fa[sequential_j][index_j_to_i];
461  for (const auto & dof_deriv : _dfa[sequential_j][index_j_to_i])
462  _dfa[sequential_i][j][dof_deriv.first] = -dof_deriv.second;
463  for (std::size_t k = 0; k < num_con_i; ++k)
464  _dFij_dKik[sequential_i][j][k] = -_dFij_dKjk[sequential_j][index_j_to_i][k];
465  const std::size_t num_con_j =
467  for (std::size_t k = 0; k < num_con_j; ++k)
468  _dFij_dKjk[sequential_i][j][k] = -_dFij_dKik[sequential_j][index_j_to_i][k];
469  }
470  }
471  }
472 
473  // zero _flux_out and its derivatives
474  _flux_out.assign(_number_of_nodes, 0.0);
475  // The derivatives are a bit complicated.
476  // If i is upwind of a node "j" then _flux_out[i] depends on all nodes connected to i.
477  // But if i is downwind of a node "j" then _flux_out depends on all nodes connected with node
478  // j.
479  _dflux_out_du.assign(_number_of_nodes, std::map<dof_id_type, Real>());
480  for (dof_id_type sequential_i = 0; sequential_i < _number_of_nodes; ++sequential_i)
481  for (const auto & j : _connections.globalConnectionsToSequentialID(sequential_i))
482  {
483  _dflux_out_du[sequential_i][j] = 0.0;
484  for (const auto & neighbors_j : _connections.globalConnectionsToGlobalID(j))
485  _dflux_out_du[sequential_i][neighbors_j] = 0.0;
486  }
488  for (dof_id_type sequential_i = 0; sequential_i < _number_of_nodes; ++sequential_i)
489  {
490  const std::vector<dof_id_type> & con_i =
492  const std::size_t num_con_i = con_i.size();
493  _dflux_out_dKjk[sequential_i].resize(num_con_i);
494  for (std::size_t j = 0; j < num_con_i; ++j)
495  {
496  const dof_id_type sequential_j = con_i[j];
497  const std::vector<dof_id_type> & con_j =
499  _dflux_out_dKjk[sequential_i][j].assign(con_j.size(), 0.0);
500  }
501  }
502 
503  // Add everything together
504  // See step 3 in Fig 2, noting Eqn (36)
505  for (dof_id_type sequential_i = 0; sequential_i < _number_of_nodes; ++sequential_i)
506  {
507  const std::vector<dof_id_type> & con_i =
509  const size_t num_con_i = con_i.size();
510  const dof_id_type index_i_to_i =
511  _connections.indexOfSequentialConnection(sequential_i, sequential_i);
512  for (std::size_t j = 0; j < num_con_i; ++j)
513  {
514  const dof_id_type sequential_j = con_i[j];
515  const dof_id_type global_j = _connections.globalID(sequential_j);
516  const Real u_j = _u_nodal[sequential_j];
517 
518  // negative sign because residual = -Lu (KT equation (19))
519  _flux_out[sequential_i] -= _lij[sequential_i][j] * u_j + _fa[sequential_i][j];
520 
521  _dflux_out_du[sequential_i][global_j] -= _lij[sequential_i][j];
522  for (const auto & dof_deriv : _dfa[sequential_i][j])
523  _dflux_out_du[sequential_i][dof_deriv.first] -= dof_deriv.second;
524 
525  _dflux_out_dKjk[sequential_i][index_i_to_i][j] -= 1.0 * u_j; // from the K in L = K + D
526 
527  if (sequential_j == sequential_i)
528  for (dof_id_type k = 0; k < num_con_i; ++k)
529  _dflux_out_dKjk[sequential_i][index_i_to_i][k] -= _dDii_dKij[sequential_i][k] * u_j;
530  else
531  _dflux_out_dKjk[sequential_i][index_i_to_i][j] -= _dDij_dKij[sequential_i][j] * u_j;
532  for (dof_id_type k = 0; k < num_con_i; ++k)
533  _dflux_out_dKjk[sequential_i][index_i_to_i][k] -= _dFij_dKik[sequential_i][j][k];
534 
535  if (sequential_j == sequential_i)
536  for (unsigned k = 0; k < con_i.size(); ++k)
537  {
538  const unsigned index_k_to_i =
539  _connections.indexOfSequentialConnection(con_i[k], sequential_i);
540  _dflux_out_dKjk[sequential_i][k][index_k_to_i] -= _dDii_dKji[sequential_i][k] * u_j;
541  }
542  else
543  {
544  const unsigned index_j_to_i =
545  _connections.indexOfSequentialConnection(sequential_j, sequential_i);
546  _dflux_out_dKjk[sequential_i][j][index_j_to_i] -= _dDij_dKji[sequential_i][j] * u_j;
547  }
548  for (unsigned k = 0;
549  k < _connections.sequentialConnectionsToSequentialID(sequential_j).size();
550  ++k)
551  _dflux_out_dKjk[sequential_i][j][k] -= _dFij_dKjk[sequential_i][j][k];
552  }
553  }
554 }
555 
556 Real
558  std::vector<Real> & dlimited_du,
559  std::vector<Real> & dlimited_dk) const
560 {
561  const std::size_t num_con = _connections.sequentialConnectionsToSequentialID(sequential_i).size();
562  dlimited_du.assign(num_con, 0.0);
563  dlimited_dk.assign(num_con, 0.0);
565  return 0.0;
566  std::vector<Real> dp_du;
567  std::vector<Real> dp_dk;
568  const Real p = PQPlusMinus(sequential_i, PQPlusMinusEnum::PPlus, dp_du, dp_dk);
569  if (p == 0.0)
570  // Comment after Eqn (49): if P=0 then there's no antidiffusion, so no need to remove it
571  return 1.0;
572  std::vector<Real> dq_du;
573  std::vector<Real> dq_dk;
574  const Real q = PQPlusMinus(sequential_i, PQPlusMinusEnum::QPlus, dq_du, dq_dk);
575 
576  const Real r = q / p;
577  Real limited;
578  Real dlimited_dr;
579  limitFlux(1.0, r, limited, dlimited_dr);
580 
581  const Real p2 = std::pow(p, 2);
582  for (std::size_t j = 0; j < num_con; ++j)
583  {
584  const Real dr_du = dq_du[j] / p - q * dp_du[j] / p2;
585  const Real dr_dk = dq_dk[j] / p - q * dp_dk[j] / p2;
586  dlimited_du[j] = dlimited_dr * dr_du;
587  dlimited_dk[j] = dlimited_dr * dr_dk;
588  }
589  return limited;
590 }
591 
592 Real
594  std::vector<Real> & dlimited_du,
595  std::vector<Real> & dlimited_dk) const
596 {
597  const std::size_t num_con = _connections.sequentialConnectionsToSequentialID(sequential_i).size();
598  dlimited_du.assign(num_con, 0.0);
599  dlimited_dk.assign(num_con, 0.0);
601  return 0.0;
602  std::vector<Real> dp_du;
603  std::vector<Real> dp_dk;
604  const Real p = PQPlusMinus(sequential_i, PQPlusMinusEnum::PMinus, dp_du, dp_dk);
605  if (p == 0.0)
606  // Comment after Eqn (49): if P=0 then there's no antidiffusion, so no need to remove it
607  return 1.0;
608  std::vector<Real> dq_du;
609  std::vector<Real> dq_dk;
610  const Real q = PQPlusMinus(sequential_i, PQPlusMinusEnum::QMinus, dq_du, dq_dk);
611 
612  const Real r = q / p;
613  Real limited;
614  Real dlimited_dr;
615  limitFlux(1.0, r, limited, dlimited_dr);
616 
617  const Real p2 = std::pow(p, 2);
618  for (std::size_t j = 0; j < num_con; ++j)
619  {
620  const Real dr_du = dq_du[j] / p - q * dp_du[j] / p2;
621  const Real dr_dk = dq_dk[j] / p - q * dp_dk[j] / p2;
622  dlimited_du[j] = dlimited_dr * dr_du;
623  dlimited_dk[j] = dlimited_dr * dr_dk;
624  }
625  return limited;
626 }
627 
628 void
629 AdvectiveFluxCalculatorBase::limitFlux(Real a, Real b, Real & limited, Real & dlimited_db) const
630 {
631  limited = 0.0;
632  dlimited_db = 0.0;
634  return;
635 
636  if ((a >= 0.0 && b <= 0.0) || (a <= 0.0 && b >= 0.0))
637  return;
638  const Real s = (a > 0.0 ? 1.0 : -1.0);
639 
640  const Real lal = std::abs(a);
641  const Real lbl = std::abs(b);
642  const Real dlbl = (b >= 0.0 ? 1.0 : -1.0); // d(lbl)/db
643  switch (_flux_limiter_type)
644  {
646  {
647  if (lal <= lbl)
648  {
649  limited = s * lal;
650  dlimited_db = 0.0;
651  }
652  else
653  {
654  limited = s * lbl;
655  dlimited_db = s * dlbl;
656  }
657  return;
658  }
660  {
661  limited = s * 2 * lal * lbl / (lal + lbl);
662  dlimited_db = s * 2 * lal * (dlbl / (lal + lbl) - lbl * dlbl / std::pow(lal + lbl, 2));
663  return;
664  }
666  {
667  const Real av = 0.5 * std::abs(a + b);
668  if (2 * lal <= av && lal <= lbl)
669  {
670  // 2 * lal is the smallest
671  limited = s * 2.0 * lal;
672  dlimited_db = 0.0;
673  }
674  else if (2 * lbl <= av && lbl <= lal)
675  {
676  // 2 * lbl is the smallest
677  limited = s * 2.0 * lbl;
678  dlimited_db = s * 2.0 * dlbl;
679  }
680  else
681  {
682  // av is the smallest
683  limited = s * av;
684  // if (a>0 and b>0) then d(av)/db = 0.5 = 0.5 * dlbl
685  // if (a<0 and b<0) then d(av)/db = -0.5 = 0.5 * dlbl
686  // if a and b have different sign then limited=0, above
687  dlimited_db = s * 0.5 * dlbl;
688  }
689  return;
690  }
692  {
693  const Real term1 = std::min(2.0 * lal, lbl);
694  const Real term2 = std::min(lal, 2.0 * lbl);
695  if (term1 >= term2)
696  {
697  if (2.0 * lal <= lbl)
698  {
699  limited = s * 2 * lal;
700  dlimited_db = 0.0;
701  }
702  else
703  {
704  limited = s * lbl;
705  dlimited_db = s * dlbl;
706  }
707  }
708  else
709  {
710  if (lal <= 2.0 * lbl)
711  {
712  limited = s * lal;
713  dlimited_db = 0.0;
714  }
715  else
716  {
717  limited = s * 2.0 * lbl;
718  dlimited_db = s * 2.0 * dlbl;
719  }
720  }
721  return;
722  }
723  default:
724  return;
725  }
726 }
727 
728 const std::map<dof_id_type, Real> &
730 {
731  return _dflux_out_du[_connections.sequentialID(node_i)];
732 }
733 
734 const std::vector<std::vector<Real>> &
736 {
737  return _dflux_out_dKjk[_connections.sequentialID(node_i)];
738 }
739 
740 Real
742 {
743  return _flux_out[_connections.sequentialID(node_i)];
744 }
745 
746 unsigned
748 {
749  return _valence[_connections.sequentialID(node_i)];
750 }
751 
752 void
753 AdvectiveFluxCalculatorBase::zeroedConnection(std::map<dof_id_type, Real> & the_map,
754  dof_id_type node_i) const
755 {
756  the_map.clear();
757  for (const auto & node_j : _connections.globalConnectionsToGlobalID(node_i))
758  the_map[node_j] = 0.0;
759 }
760 
761 Real
763  const PQPlusMinusEnum pq_plus_minus,
764  std::vector<Real> & derivs,
765  std::vector<Real> & dpqdk) const
766 {
767  // Find the value of u at sequential_i
768  const Real u_i = _u_nodal[sequential_i];
769 
770  // Connections to sequential_i
771  const std::vector<dof_id_type> con_i =
773  const std::size_t num_con = con_i.size();
774  // The neighbor number of sequential_i to sequential_i
775  const unsigned i_index_i = _connections.indexOfSequentialConnection(sequential_i, sequential_i);
776 
777  // Initialize the results
778  Real result = 0.0;
779  derivs.assign(num_con, 0.0);
780  dpqdk.assign(num_con, 0.0);
781 
782  // Sum over all nodes connected with node_i.
783  for (std::size_t j = 0; j < num_con; ++j)
784  {
785  const dof_id_type sequential_j = con_i[j];
786  if (sequential_j == sequential_i)
787  continue;
788  const Real kentry = _kij[sequential_i][j];
789 
790  // Find the value of u at node_j
791  const Real u_j = _u_nodal[sequential_j];
792  const Real ujminusi = u_j - u_i;
793 
794  // Evaluate the i-j contribution to the result
795  switch (pq_plus_minus)
796  {
798  {
799  if (ujminusi < 0.0 && kentry < 0.0)
800  {
801  result += kentry * ujminusi;
802  derivs[j] += kentry;
803  derivs[i_index_i] -= kentry;
804  dpqdk[j] += ujminusi;
805  }
806  break;
807  }
809  {
810  if (ujminusi > 0.0 && kentry < 0.0)
811  {
812  result += kentry * ujminusi;
813  derivs[j] += kentry;
814  derivs[i_index_i] -= kentry;
815  dpqdk[j] += ujminusi;
816  }
817  break;
818  }
820  {
821  if (ujminusi > 0.0 && kentry > 0.0)
822  {
823  result += kentry * ujminusi;
824  derivs[j] += kentry;
825  derivs[i_index_i] -= kentry;
826  dpqdk[j] += ujminusi;
827  }
828  break;
829  }
831  {
832  if (ujminusi < 0.0 && kentry > 0.0)
833  {
834  result += kentry * ujminusi;
835  derivs[j] += kentry;
836  derivs[i_index_i] -= kentry;
837  dpqdk[j] += ujminusi;
838  }
839  break;
840  }
841  }
842  }
843 
844  return result;
845 }
846 
847 void
849 {
863  _nodes_to_receive.clear();
864  for (const auto & elem : _fe_problem.getNonlinearEvaluableElementRange())
865  if (this->hasBlocks(elem->subdomain_id()))
866  {
867  const processor_id_type elem_pid = elem->processor_id();
868  if (elem_pid != _my_pid)
869  {
870  if (_nodes_to_receive.find(elem_pid) == _nodes_to_receive.end())
871  _nodes_to_receive[elem_pid] = std::vector<dof_id_type>();
872  for (unsigned i = 0; i < elem->n_nodes(); ++i)
873  if (std::find(_nodes_to_receive[elem_pid].begin(),
874  _nodes_to_receive[elem_pid].end(),
875  elem->node_id(i)) == _nodes_to_receive[elem_pid].end())
876  _nodes_to_receive[elem_pid].push_back(elem->node_id(i));
877  }
878  }
879 
880  // exchange this info with other processors, building _nodes_to_send at the same time
881  _nodes_to_send.clear();
882  auto nodes_action_functor = [this](processor_id_type pid, const std::vector<dof_id_type> & nts)
883  { _nodes_to_send[pid] = nts; };
884  Parallel::push_parallel_vector_data(this->comm(), _nodes_to_receive, nodes_action_functor);
885 
886  // At the moment, _nodes_to_send and _nodes_to_receive contain global node numbers
887  // It is slightly more efficient to convert to sequential node numbers
888  // so that we don't have to keep doing things like
889  // _u_nodal[_connections.sequentialID(_nodes_to_send[pid][i])
890  // every time we send/receive
891  for (auto & kv : _nodes_to_send)
892  {
893  const processor_id_type pid = kv.first;
894  const std::size_t num_nodes = kv.second.size();
895  for (unsigned i = 0; i < num_nodes; ++i)
897  }
898  for (auto & kv : _nodes_to_receive)
899  {
900  const processor_id_type pid = kv.first;
901  const std::size_t num_nodes = kv.second.size();
902  for (unsigned i = 0; i < num_nodes; ++i)
904  }
905 
906  // Build pairs_to_receive
907  _pairs_to_receive.clear();
908  for (const auto & elem : _fe_problem.getNonlinearEvaluableElementRange())
909  if (this->hasBlocks(elem->subdomain_id()))
910  {
911  const processor_id_type elem_pid = elem->processor_id();
912  if (elem_pid != _my_pid)
913  {
914  if (_pairs_to_receive.find(elem_pid) == _pairs_to_receive.end())
915  _pairs_to_receive[elem_pid] = std::vector<std::pair<dof_id_type, dof_id_type>>();
916  for (unsigned i = 0; i < elem->n_nodes(); ++i)
917  for (unsigned j = 0; j < elem->n_nodes(); ++j)
918  {
919  std::pair<dof_id_type, dof_id_type> the_pair(elem->node_id(i), elem->node_id(j));
920  if (std::find(_pairs_to_receive[elem_pid].begin(),
921  _pairs_to_receive[elem_pid].end(),
922  the_pair) == _pairs_to_receive[elem_pid].end())
923  _pairs_to_receive[elem_pid].push_back(the_pair);
924  }
925  }
926  }
927 
928  _pairs_to_send.clear();
929  auto pairs_action_functor =
930  [this](processor_id_type pid, const std::vector<std::pair<dof_id_type, dof_id_type>> & pts)
931  { _pairs_to_send[pid] = pts; };
932  Parallel::push_parallel_vector_data(this->comm(), _pairs_to_receive, pairs_action_functor);
933 
934  // _pairs_to_send and _pairs_to_receive have been built using global node IDs
935  // since all processors know about that. However, using global IDs means
936  // that every time we send/receive, we keep having to do things like
937  // _kij[_connections.sequentialID(_pairs_to_send[pid][i].first)][_connections.indexOfGlobalConnection(_pairs_to_send[pid][i].first,
938  // _pairs_to_send[pid][i].second)] which is quite inefficient. So:
939  for (auto & kv : _pairs_to_send)
940  {
941  const processor_id_type pid = kv.first;
942  const std::size_t num_pairs = kv.second.size();
943  for (unsigned i = 0; i < num_pairs; ++i)
944  {
946  _pairs_to_send[pid][i].first, _pairs_to_send[pid][i].second);
947  _pairs_to_send[pid][i].first = _connections.sequentialID(_pairs_to_send[pid][i].first);
948  }
949  }
950  for (auto & kv : _pairs_to_receive)
951  {
952  const processor_id_type pid = kv.first;
953  const std::size_t num_pairs = kv.second.size();
954  for (unsigned i = 0; i < num_pairs; ++i)
955  {
957  _pairs_to_receive[pid][i].first, _pairs_to_receive[pid][i].second);
958  _pairs_to_receive[pid][i].first = _connections.sequentialID(_pairs_to_receive[pid][i].first);
959  }
960  }
961 }
962 
963 void
965 {
966  // Exchange ghosted _u_nodal information with other processors
967  std::map<processor_id_type, std::vector<Real>> unodal_to_send;
968  for (const auto & kv : _nodes_to_send)
969  {
970  const processor_id_type pid = kv.first;
971  unodal_to_send[pid] = std::vector<Real>();
972  for (const auto & nd : kv.second)
973  unodal_to_send[pid].push_back(_u_nodal[nd]);
974  }
975 
976  auto unodal_action_functor =
977  [this](processor_id_type pid, const std::vector<Real> & unodal_received)
978  {
979  const std::size_t msg_size = unodal_received.size();
980  mooseAssert(msg_size == _nodes_to_receive[pid].size(),
981  "Message size, " << msg_size
982  << ", incompatible with nodes_to_receive, which has size "
983  << _nodes_to_receive[pid].size());
984  for (unsigned i = 0; i < msg_size; ++i)
985  _u_nodal[_nodes_to_receive[pid][i]] = unodal_received[i];
986  };
987  Parallel::push_parallel_vector_data(this->comm(), unodal_to_send, unodal_action_functor);
988 
989  // Exchange _kij information with other processors
990  std::map<processor_id_type, std::vector<Real>> kij_to_send;
991  for (const auto & kv : _pairs_to_send)
992  {
993  const processor_id_type pid = kv.first;
994  kij_to_send[pid] = std::vector<Real>();
995  for (const auto & pr : kv.second)
996  kij_to_send[pid].push_back(_kij[pr.first][pr.second]);
997  }
998 
999  auto kij_action_functor = [this](processor_id_type pid, const std::vector<Real> & kij_received)
1000  {
1001  const std::size_t msg_size = kij_received.size();
1002  mooseAssert(msg_size == _pairs_to_receive[pid].size(),
1003  "Message size, " << msg_size
1004  << ", incompatible with pairs_to_receive, which has size "
1005  << _pairs_to_receive[pid].size());
1006  for (unsigned i = 0; i < msg_size; ++i)
1007  _kij[_pairs_to_receive[pid][i].first][_pairs_to_receive[pid][i].second] += kij_received[i];
1008  };
1009  Parallel::push_parallel_vector_data(this->comm(), kij_to_send, kij_action_functor);
1010 }
unsigned getValence(dof_id_type node_i) const
Returns the valence of the global node i Valence is the number of times the node is encountered in a ...
std::vector< std::vector< Real > > _dDij_dKij
dDij_dKij[i][j] = d(D[i][j])/d(K[i][j]) for i!=j
void clear()
clear all data in readiness for adding global nodes and connections
std::vector< bool > _u_nodal_computed_by_thread
_u_nodal_computed_by_thread(i) = true if _u_nodal[i] has been computed in execute() by the thread on ...
std::vector< std::vector< std::vector< Real > > > _dFij_dKjk
dFij_dKjk[sequential_i][j][k] = d(fa[sequential_i][j])/d(K[sequential_j][k]).
FluxLimiterTypeEnum
Determines Flux Limiter type (Page 135 of Kuzmin and Turek) "None" means that limitFlux=0 always...
dof_id_type globalID(dof_id_type sequential_node_ID) const
Return the global node ID (node number in the mesh) corresponding to the provided sequential node ID...
Real getFluxOut(dof_id_type node_i) const
Returns the flux out of lobal node id.
const MooseArray< Real > & _coord
void addParam(const std::string &name, const std::initializer_list< typename T::value_type > &value, const std::string &doc_string)
virtual void meshChanged()
static InputParameters validParams()
void limitFlux(Real a, Real b, Real &limited, Real &dlimited_db) const
flux limiter, L, on Page 135 of Kuzmin and Turek
std::vector< std::vector< std::map< dof_id_type, Real > > > _dfa
dfa[sequential_i][j][global_k] = d(fa[sequential_i][j])/du[global_k].
std::vector< std::map< dof_id_type, Real > > _dflux_out_du
_dflux_out_du[i][j] = d(flux_out[i])/d(u[j]).
void gatherMax(T &value)
T & set(const std::string &name, bool quiet_mode=false)
void addConnection(dof_id_type global_node_from, dof_id_type global_node_to)
Specifies that global_node_to is connected to global_node_from.
dof_id_type sequentialID(dof_id_type global_node_ID) const
Return the sequential node ID corresponding to the global node ID This is guaranteed to lie in the ra...
const std::vector< dof_id_type > & sequentialConnectionsToSequentialID(dof_id_type sequential_node_ID) const
Return all the nodes (sequential node IDs) connected to the given sequential node ID All elements of ...
const Parallel::Communicator & comm() const
Real rMinus(dof_id_type sequential_i, std::vector< Real > &dlimited_du, std::vector< Real > &dlimited_dk) const
Returns the value of R_{i}^{-}, Eqn (49) of KT.
void finalizeAddingConnections()
Signal that all global node IDs have been added to the internal data structures.
unsigned indexOfGlobalConnection(dof_id_type global_node_ID_from, dof_id_type global_node_ID_to) const
Return the index of global_node_ID_to in the globalConnectionsToGlobalID(global_node_ID_from) vector...
virtual void executeOnElement(dof_id_type global_i, dof_id_type global_j, unsigned local_i, unsigned local_j, unsigned qp)
This is called by multiple times in execute() in a double loop over _current_elem&#39;s nodes (local_i an...
std::vector< std::vector< Real > > _dij
Vectors used in finalize()
std::size_t _number_of_nodes
Number of nodes held by the _connections object.
std::vector< Real > _flux_out
_flux_out[i] = flux of "heat" from sequential node i
std::vector< std::vector< std::vector< Real > > > _dflux_out_dKjk
_dflux_out_dKjk[sequential_i][j][k] = d(flux_out[sequential_i])/d(K[j][k]).
std::vector< std::vector< Real > > _dDii_dKij
dDii_dKij[i][j] = d(D[i][i])/d(K[i][j])
void addRelationshipManager(const std::string &name, Moose::RelationshipManagerType rm_type, Moose::RelationshipManagerInputParameterCallback input_parameter_callback=nullptr)
virtual const std::string & name() const
void mooseWarning(Args &&... args) const
std::vector< std::vector< Real > > _dDii_dKji
dDii_dKji[i][j] = d(D[i][i])/d(K[j][i])
Real PQPlusMinus(dof_id_type sequential_i, const PQPlusMinusEnum pq_plus_minus, std::vector< Real > &derivs, std::vector< Real > &dpq_dk) const
Returns the value of P_{i}^{+}, P_{i}^{-}, Q_{i}^{+} or Q_{i}^{-} (depending on pq_plus_minus) which ...
const std::vector< dof_id_type > & globalConnectionsToSequentialID(dof_id_type sequential_node_ID) const
Return all the nodes (global node IDs) connected to the given sequential node ID. ...
ADRealEigenVector< T, D, asd > abs(const ADRealEigenVector< T, D, asd > &)
uint8_t processor_id_type
bool contains(const std::string &value) const
processor_id_type n_processors() const
std::size_t sizeSequential() const
Return the size of _sequential_id, for checking memory efficiency.
static InputParameters validParams()
Base class to compute Advective fluxes.
enum AdvectiveFluxCalculatorBase::FluxLimiterTypeEnum _flux_limiter_type
PorousFlowConnectedNodes _connections
Holds the sequential and global nodal IDs, and info regarding mesh connections between them...
bool _resizing_needed
whether _kij, etc, need to be sized appropriately (and valence recomputed) at the start of the timest...
std::map< processor_id_type, std::vector< dof_id_type > > _nodes_to_send
_nodes_to_send[proc_id] = list of sequential nodal IDs.
std::vector< std::vector< Real > > _drM_dk
drM_dk[i][j] = d(rM[i])/d(K[i][j]). Here j indexes the j^th node connected to i
const std::map< dof_id_type, Real > & getdFluxOutdu(dof_id_type node_i) const
Returns r where r[j] = d(flux out of global node i)/du(global node j) used in Jacobian computations...
std::vector< std::vector< Real > > _drM
drM[i][j] = d(rM[i])/d(u[j]). Here j indexes the j^th node connected to i
const std::vector< std::vector< Real > > & getdFluxOutdKjk(dof_id_type node_i) const
Returns r where r[j][k] = d(flux out of global node i)/dK[connected node j][connected node k] used in...
void paramError(const std::string &param, Args... args) const
Real rPlus(dof_id_type sequential_i, std::vector< Real > &dlimited_du, std::vector< Real > &dlimited_dk) const
Returns the value of R_{i}^{+}, Eqn (49) of KT.
const ExecFlagType EXEC_LINEAR
std::map< processor_id_type, std::vector< std::pair< dof_id_type, dof_id_type > > > _pairs_to_send
_pairs_to_send[proc_id] indicates the k(i, j) pairs that we will send to proc_id _pairs_to_send is fi...
std::string stringify(const T &t)
std::vector< Real > _u_nodal
_u_nodal[i] = value of _u at sequential node number i
processor_id_type _my_pid
processor ID of this object
virtual void exchangeGhostedInfo()
Sends and receives multi-processor information regarding u_nodal and k_ij.
const ExecFlagEnum & _execute_enum
const Real _allowable_MB_wastage
A mooseWarning is issued if mb_wasted = (_connections.sizeSequential() - _connections.numNodes()) * 4 / 1048576 > _allowable_MB_wastage.
virtual Real computeVelocity(unsigned i, unsigned j, unsigned qp) const =0
Computes the transfer velocity between current node i and current node j at the current qp in the cur...
virtual Real computeU(unsigned i) const =0
Computes the value of u at the local node id of the current element (_current_elem) ...
std::size_t numNodes() const
number of nodes known by this class
std::vector< std::vector< Real > > _drP_dk
drP_dk[i][j] = d(rP[i])/d(K[i][j]). Here j indexes the j^th node connected to i
DIE A HORRIBLE DEATH HERE typedef LIBMESH_DEFAULT_SCALAR_TYPE Real
const QBase *const & _qrule
const Elem *const & _current_elem
std::vector< std::vector< std::vector< Real > > > _dFij_dKik
dFij_dKik[sequential_i][j][k] = d(fa[sequential_i][j])/d(K[sequential_i][k]).
FEProblemBase & _fe_problem
AdvectiveFluxCalculatorBase(const InputParameters &parameters)
const MooseArray< Real > & _JxW
std::vector< std::vector< Real > > _lij
virtual void buildCommLists()
When using multiple processors, other processors will compute:
std::vector< std::vector< Real > > _kij
Kuzmin-Turek K_ij matrix.
void addClassDescription(const std::string &doc_string)
static const std::complex< double > j(0, 1)
Complex number "j" (also known as "i")
std::map< processor_id_type, std::vector< dof_id_type > > _nodes_to_receive
_nodes_to_receive[proc_id] = list of sequential nodal IDs.
void addRangeCheckedParam(const std::string &name, const T &value, const std::string &parsed_function, const std::string &doc_string)
PQPlusMinusEnum
Signals to the PQPlusMinus method what should be computed.
std::map< processor_id_type, std::vector< std::pair< dof_id_type, dof_id_type > > > _pairs_to_receive
_pairs_to_receive[proc_id] indicates the k(i, j) pairs that will be sent to us from proc_id _pairs_to...
const std::vector< dof_id_type > & globalConnectionsToGlobalID(dof_id_type global_node_ID) const
Return all the nodes (global node IDs) connected to the given global node ID.
void finalizeAddingGlobalNodes()
Signal that all global node IDs have been added to the internal data structures.
bool hasBlocks(const SubdomainName &name) const
void zeroedConnection(std::map< dof_id_type, Real > &the_map, dof_id_type node_i) const
Clears the_map, then, using _kij, constructs the_map so that the_map[node_id] = 0.0 for all node_id connected with node_i.
const ConstElemRange & getNonlinearEvaluableElementRange()
std::vector< unsigned > _valence
_valence[i] = number of times, in a loop over elements seen by this processor (viz, including ghost elements) and are part of the block-restricted blocks of this UserObject, that the sequential node i is encountered
std::vector< std::vector< Real > > _dDij_dKji
dDij_dKji[i][j] = d(D[i][j])/d(K[j][i]) for i!=j
virtual void threadJoin(const UserObject &uo) override
MooseUnits pow(const MooseUnits &, int)
std::vector< std::vector< Real > > _fa
fa[sequential_i][j] sequential_j is the j^th connection to sequential_i
static const std::string k
Definition: NS.h:124
void addGlobalNode(dof_id_type global_node_ID)
Add the given global_node_ID to the internal data structures If the global node ID has already been a...
std::vector< std::vector< Real > > _drP
drP[i][j] = d(rP[i])/d(u[j]). Here j indexes the j^th node connected to i
unsigned indexOfSequentialConnection(dof_id_type sequential_node_ID_from, dof_id_type sequential_node_ID_to) const
Return the index of sequential_node_ID_to in the sequentialConnectionsToSequentialID(sequential_node_...
uint8_t dof_id_type