NonDGlobalReliability Class Reference

Class for global reliability methods within DAKOTA/UQ. More...

Inheritance diagram for NonDGlobalReliability:

List of all members.

Public Member Functions
	NonDGlobalReliability (ProblemDescDB &problem_db, Model &model)
	constructor
	~NonDGlobalReliability ()
	destructor
void	derived_init_communicators (ParLevLIter pl_iter)
	derived class contributions to initializing the communicators associated with this Iterator instance
void	derived_set_communicators (ParLevLIter pl_iter)
	derived class contributions to setting the communicators associated with this Iterator instance
void	derived_free_communicators (ParLevLIter pl_iter)
	derived class contributions to freeing the communicators associated with this Iterator instance
void	quantify_uncertainty ()
	performs an uncertainty propagation using analytical reliability methods which solve constrained optimization problems to obtain approximations of the cumulative distribution function of response
void	print_results (std::ostream &s)
	print the approximate mean, standard deviation, and importance factors when using the mean value method or the CDF/CCDF information when using MPP-search-based reliability methods
Private Member Functions
void	optimize_gaussian_process ()
	construct the GP using EGO/SKO
void	importance_sampling ()
	perform multimodal adaptive importance sampling on the GP
void	get_best_sample ()
	determine current best solution from among sample data for expected imporovement function in Performance Measure Approach (PMA)
Real	constraint_penalty (const Real &constraint, const RealVector &c_variables)
	calculate the penalty to be applied to the PMA constraint value
Real	expected_improvement (const RealVector &expected_values, const Variables &recast_vars)
	expected improvement function for the GP
Real	expected_feasibility (const RealVector &expected_values, const Variables &recast_vars)
	expected feasibility function for the GP
Static Private Member Functions
static void	EIF_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 Expected Improvement (EIF) problem formulation for PMA
static void	EFF_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 Expected Feasibility (EFF) problem formulation for RIA
Private Attributes
Real	fnStar
	minimum penalized response from among true function evaluations
short	meritFunctionType
	type of merit function used to penalize sample data
Real	lagrangeMult
	Lagrange multiplier for standard Lagrangian merit function.
Real	augLagrangeMult
	Lagrange multiplier for augmented Lagrangian merit function.
Real	penaltyParameter
	penalty parameter for augmented Lagrangian merit funciton
Real	lastConstraintViolation
	constraint violation at last iteration, used to determine if the current iterate should be accepted (must reduce violation)
bool	lastIterateAccepted
	flag to determine if last iterate was accepted this controls update of parameters for augmented Lagrangian merit fn
short	dataOrder
	order of the data used for surrogate construction, in ActiveSet request vector 3-bit format; user may override responses spec
Static Private Attributes
static NonDGlobalReliability *	nondGlobRelInstance
	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

Class for global reliability methods within DAKOTA/UQ.

The NonDGlobalReliability class implements EGO/SKO for global MPP search, which maximizes an expected improvement function derived from Gaussian process models. Once the limit state has been characterized, a multimodal importance sampling approach is used to compute probabilities.

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

• NonDGlobalReliability.hpp
• NonDGlobalReliability.cpp