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Dakota
Version 6.2
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Base class for the reliability methods within DAKOTA/UQ. More...
Protected Member Functions | |
NonDReliability (ProblemDescDB &problem_db, Model &model) | |
constructor | |
~NonDReliability () | |
destructor | |
void | initialize_graphics (int iterator_server_id=1) |
initialize graphics customized for reliability methods | |
const Model & | algorithm_space_model () const |
Protected Attributes | |
Model | uSpaceModel |
Model representing the limit state in u-space, after any recastings and data fits. | |
Model | mppModel |
RecastModel which formulates the optimization subproblem: RIA, PMA, EGO. | |
Iterator | mppOptimizer |
Iterator which optimizes the mppModel. | |
unsigned short | mppSearchType |
the MPP search type selection: MV, x/u-space AMV, x/u-space AMV+, x/u-space TANA, x/u-space EGO, or NO_APPROX | |
Iterator | importanceSampler |
importance sampling instance used to compute/refine probabilities | |
unsigned short | integrationRefinement |
integration refinement type (NO_INT_REFINE, IS, AIS, or MMAIS) provided by refinement specification | |
size_t | numRelAnalyses |
number of invocations of quantify_uncertainty() | |
size_t | approxIters |
number of approximation cycles for the current respFnCount/levelCount | |
bool | approxConverged |
indicates convergence of approximation-based iterations | |
int | respFnCount |
counter for which response function is being analyzed | |
size_t | levelCount |
counter for which response/probability level is being analyzed | |
size_t | statCount |
counter for which final statistic is being computed | |
bool | pmaMaximizeG |
flag indicating maximization of G(u) within PMA formulation | |
Real | requestedTargetLevel |
the {response,reliability,generalized reliability} level target for the current response function |
Base class for the reliability methods within DAKOTA/UQ.
The NonDReliability class provides a base class for NonDLocalReliability, which implements traditional MPP-based reliability methods, and NonDGlobalReliability, which implements global limit state search using Gaussian process models in combination with multimodal importance sampling.
const Model & algorithm_space_model | ( | ) | const [inline, protected, virtual] |
default definition that gets redefined in selected derived Minimizers
Reimplemented from Analyzer.
References NonDReliability::uSpaceModel.