NonDReliability Class Reference

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

Inheritance diagram for NonDReliability:

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
const Model &	algorithm_space_model () const
	return the result of any recasting or surrogate model recursion layered on top of iteratedModel by the derived Iterator ctor chain
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 Variables &recast_vars, 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 NonDReliability *	nondRelInstance
	pointer to the active object instance used within the static evaluator functions in order to avoid the need for static data

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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.

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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_view(), Response::function_hessian_view(), 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_gradient_view(), Response::function_hessian(), Response::function_value(), 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_gradient_view(), Response::function_gradients(), Response::function_hessian(), Response::function_hessian_view(), Response::function_value(), 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_view(), Response::function_hessian_view(), Response::function_value(), NonDReliability::nondRelInstance, NonDReliability::requestedCDFRelLevel, and NonDReliability::update_pma_reliability_level().

Referenced by NonDLocalReliability::mpp_search().

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

• NonDReliability.H
• NonDReliability.C