Protected Member Functions | Static Protected Member Functions | Protected Attributes | Static Protected Attributes
NonDReliability Class Reference

Base class for the reliability methods within DAKOTA/UQ. More...

Inheritance diagram for NonDReliability:
NonD Analyzer Iterator NonDGlobalReliability NonDLocalReliability

List of all members.

Protected Member Functions

 NonDReliability (Model &model)
 constructor
 ~NonDReliability ()
 destructor
void initialize_graphics (bool graph_2d, bool tabular_data, const String &tabular_file)
 initialize graphics customized for reliability methods
virtual void update_pma_reliability_level ()
 update requestedCDFRelLevel for use in PMA_constraint_eval()

Static Protected Member Functions

static void RIA_objective_eval (const Variables &sub_model_vars, const Variables &recast_vars, const Response &sub_model_response, Response &recast_response)
 static function used as the objective function in the Reliability Index Approach (RIA) problem formulation. This equality-constrained optimization problem performs the search for the most probable point (MPP) with the objective function of (norm u)^2.
static void RIA_constraint_eval (const Variables &sub_model_vars, const Variables &recast_vars, const Response &sub_model_response, Response &recast_response)
 static function used as the constraint function in the Reliability Index Approach (RIA) problem formulation. This equality-constrained optimization problem performs the search for the most probable point (MPP) with the constraint of G(u) = response level.
static void PMA_objective_eval (const Variables &sub_model_vars, const Variables &recast_vars, const Response &sub_model_response, Response &recast_response)
 static function used as the objective function in the Performance Measure Approach (PMA) problem formulation. This equality-constrained optimization problem performs the search for the most probable point (MPP) with the objective function of G(u).
static void PMA_constraint_eval (const Variables &sub_model_vars, const Variables &recast_vars, const Response &sub_model_response, Response &recast_response)
 static function used as the constraint function in the Performance Measure Approach (PMA) problem formulation. This equality-constrained optimization problem performs the search for the most probable point (MPP) with the constraint of (norm u)^2 = beta^2.
static void PMA2_set_mapping (const ActiveSet &recast_set, ActiveSet &sub_model_set)
 static function used to augment the sub-model ASV requests when a beta-bar constraint target update is required for second-order PMA

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.
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
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
Real requestedRespLevel
 the response level target for the current response function
Real requestedCDFProbLevel
 the CDF probability level target for the current response function
Real requestedCDFRelLevel
 the CDF reliability level target for the current response function
Real computedRespLevel
 output response level calculated
Real computedRelLevel
 output reliability level calculated

Static Protected Attributes

static NonDReliabilitynondRelInstance
 pointer to the active object instance used within the static evaluator functions in order to avoid the need for static data

Detailed Description

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.


Member Function Documentation

void RIA_objective_eval ( const Variables sub_model_vars,
const Variables recast_vars,
const Response sub_model_response,
Response recast_response 
) [static, protected]

static function used as the objective function in the Reliability Index Approach (RIA) problem formulation. This equality-constrained optimization problem performs the search for the most probable point (MPP) with the objective function of (norm u)^2.

This function recasts a G(u) response set (already transformed and approximated in other recursions) into an RIA objective function.

References Response::active_set_request_vector(), Variables::continuous_variables(), Response::function_gradient(), Response::function_hessian(), and Response::function_value().

Referenced by NonDLocalReliability::mpp_search().

void RIA_constraint_eval ( const Variables sub_model_vars,
const Variables recast_vars,
const Response sub_model_response,
Response recast_response 
) [static, protected]

static function used as the constraint function in the Reliability Index Approach (RIA) problem formulation. This equality-constrained optimization problem performs the search for the most probable point (MPP) with the constraint of G(u) = response level.

This function recasts a G(u) response set (already transformed and approximated in other recursions) into an RIA equality constraint.

References Response::active_set_request_vector(), Response::function_gradient(), Response::function_hessian(), Response::function_hessians(), Response::function_value(), Response::function_values(), NonDReliability::nondRelInstance, NonDReliability::requestedRespLevel, and NonDReliability::respFnCount.

Referenced by NonDLocalReliability::mpp_search().

void PMA_objective_eval ( const Variables sub_model_vars,
const Variables recast_vars,
const Response sub_model_response,
Response recast_response 
) [static, protected]

static function used as the objective function in the Performance Measure Approach (PMA) problem formulation. This equality-constrained optimization problem performs the search for the most probable point (MPP) with the objective function of G(u).

This function recasts a G(u) response set (already transformed and approximated in other recursions) into an PMA objective function.

References Response::active_set_request_vector(), Response::function_gradient(), Response::function_gradients(), Response::function_hessian(), Response::function_hessians(), Response::function_value(), Response::function_values(), NonDReliability::nondRelInstance, NonDReliability::requestedCDFRelLevel, and NonDReliability::respFnCount.

Referenced by NonDLocalReliability::mpp_search().

void PMA_constraint_eval ( const Variables sub_model_vars,
const Variables recast_vars,
const Response sub_model_response,
Response recast_response 
) [static, protected]

static function used as the constraint function in the Performance Measure Approach (PMA) problem formulation. This equality-constrained optimization problem performs the search for the most probable point (MPP) with the constraint of (norm u)^2 = beta^2.

This function recasts a G(u) response set (already transformed and approximated in other recursions) into a PMA equality constraint.

References Response::active_set_request_vector(), Variables::continuous_variables(), Response::function_gradient(), Response::function_hessian(), Response::function_value(), NonDReliability::nondRelInstance, NonDReliability::requestedCDFRelLevel, and NonDReliability::update_pma_reliability_level().

Referenced by NonDLocalReliability::mpp_search().


The documentation for this class was generated from the following files: