FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2896671255> ?p ?o ?g. }

• W2896671255 endingPage "502" @default.
• W2896671255 startingPage "487" @default.
• W2896671255 abstract "The reliability analysis of a structural system is typically evaluated based on a multivariate model that describes the underlying mechanistic relationship between the system’s input and output random variables. This is the need to develop an effective surrogate model to mimic the input–output relationship as the Monte Carlo simulation–based on the mechanistic model might be computationally intensive. In this regard, the article presents a sparse regression method for structural reliability analysis based on the generalized polynomial chaos expansion. However, results from the global sensitivity analysis have justified that it is unnecessary to contain all polynomial terms in the surrogate model, instead of comprising a rather small number of principle components only. One direct benefit of the sparse approximation allows utilizing a small number of training samples to calibrate the surrogate model, bearing in mind that the required sample size is positively proportional to the number of unknowns in regression analysis. Therefore, by utilizing the standard polynomial chaos basis functions to constitute an explanatory dictionary, an adaptive sparse regression approach characterized by introducing the most significant explanatory variable in each iteration is presented. A statistical approach for detecting and excluding spuriously explanatory polynomials is also introduced to maintain the high sparsity of the meta-modeling result. Combined with a variety of low-discrepancy schemes in generating training samples, structural reliability and global sensitivity analysis of originally true but computationally demanding models are alternatively realized based on the sparse surrogate method in conjunction with the brutal Monte Carlo simulation method. Numerical examples are carried out to demonstrate the applicability of the sparse regression approach to structural reliability problems. Results have shown that the proposed method is an effective, non-intrusive approach to deal with uncertainty analysis of various structural systems." @default.
• W2896671255 created "2018-10-26" @default.
• W2896671255 creator A5000510528 @default.
• W2896671255 creator A5021004981 @default.
• W2896671255 creator A5027330816 @default.
• W2896671255 date "2018-10-08" @default.
• W2896671255 modified "2023-10-15" @default.
• W2896671255 title "A sparse surrogate model for structural reliability analysis based on the generalized polynomial chaos expansion" @default.
• W2896671255 cites W1572480955 @default.
• W2896671255 cites W1758879090 @default.
• W2896671255 cites W1969970422 @default.
• W2896671255 cites W1978289729 @default.
• W2896671255 cites W1978501336 @default.
• W2896671255 cites W1987464754 @default.
• W2896671255 cites W1991079954 @default.
• W2896671255 cites W1995565517 @default.
• W2896671255 cites W2002869412 @default.
• W2896671255 cites W2016312558 @default.
• W2896671255 cites W2018159038 @default.
• W2896671255 cites W2027968505 @default.
• W2896671255 cites W2043973777 @default.
• W2896671255 cites W2058542661 @default.
• W2896671255 cites W2077780148 @default.
• W2896671255 cites W2080240494 @default.
• W2896671255 cites W2087608345 @default.
• W2896671255 cites W2136602340 @default.
• W2896671255 cites W2140951396 @default.
• W2896671255 cites W2167720109 @default.
• W2896671255 cites W2321957512 @default.
• W2896671255 doi "https://doi.org/10.1177/1748006x18804047" @default.
• W2896671255 hasPublicationYear "2018" @default.
• W2896671255 type Work @default.
• W2896671255 sameAs 2896671255 @default.
• W2896671255 citedByCount "3" @default.
• W2896671255 countsByYear W28966712552019 @default.
• W2896671255 countsByYear W28966712552020 @default.
• W2896671255 crossrefType "journal-article" @default.
• W2896671255 hasAuthorship W2896671255A5000510528 @default.
• W2896671255 hasAuthorship W2896671255A5021004981 @default.
• W2896671255 hasAuthorship W2896671255A5027330816 @default.
• W2896671255 hasConcept C105795698 @default.
• W2896671255 hasConcept C11413529 @default.
• W2896671255 hasConcept C119857082 @default.
• W2896671255 hasConcept C121332964 @default.
• W2896671255 hasConcept C126255220 @default.
• W2896671255 hasConcept C127413603 @default.
• W2896671255 hasConcept C131675550 @default.
• W2896671255 hasConcept C134306372 @default.
• W2896671255 hasConcept C152877465 @default.
• W2896671255 hasConcept C163258240 @default.
• W2896671255 hasConcept C182365436 @default.
• W2896671255 hasConcept C19499675 @default.
• W2896671255 hasConcept C197656079 @default.
• W2896671255 hasConcept C21200559 @default.
• W2896671255 hasConcept C24326235 @default.
• W2896671255 hasConcept C32230216 @default.
• W2896671255 hasConcept C33923547 @default.
• W2896671255 hasConcept C41008148 @default.
• W2896671255 hasConcept C43214815 @default.
• W2896671255 hasConcept C62520636 @default.
• W2896671255 hasConcept C90119067 @default.
• W2896671255 hasConceptScore W2896671255C105795698 @default.
• W2896671255 hasConceptScore W2896671255C11413529 @default.
• W2896671255 hasConceptScore W2896671255C119857082 @default.
• W2896671255 hasConceptScore W2896671255C121332964 @default.
• W2896671255 hasConceptScore W2896671255C126255220 @default.
• W2896671255 hasConceptScore W2896671255C127413603 @default.
• W2896671255 hasConceptScore W2896671255C131675550 @default.
• W2896671255 hasConceptScore W2896671255C134306372 @default.
• W2896671255 hasConceptScore W2896671255C152877465 @default.
• W2896671255 hasConceptScore W2896671255C163258240 @default.
• W2896671255 hasConceptScore W2896671255C182365436 @default.
• W2896671255 hasConceptScore W2896671255C19499675 @default.
• W2896671255 hasConceptScore W2896671255C197656079 @default.
• W2896671255 hasConceptScore W2896671255C21200559 @default.
• W2896671255 hasConceptScore W2896671255C24326235 @default.
• W2896671255 hasConceptScore W2896671255C32230216 @default.
• W2896671255 hasConceptScore W2896671255C33923547 @default.
• W2896671255 hasConceptScore W2896671255C41008148 @default.
• W2896671255 hasConceptScore W2896671255C43214815 @default.
• W2896671255 hasConceptScore W2896671255C62520636 @default.
• W2896671255 hasConceptScore W2896671255C90119067 @default.
• W2896671255 hasFunder F4320321001 @default.
• W2896671255 hasIssue "3" @default.
• W2896671255 hasLocation W28966712551 @default.
• W2896671255 hasOpenAccess W2896671255 @default.
• W2896671255 hasPrimaryLocation W28966712551 @default.
• W2896671255 hasRelatedWork W2256307465 @default.
• W2896671255 hasRelatedWork W2756374862 @default.
• W2896671255 hasRelatedWork W2984825772 @default.
• W2896671255 hasRelatedWork W3006167044 @default.
• W2896671255 hasRelatedWork W3007901103 @default.
• W2896671255 hasRelatedWork W3132062048 @default.
• W2896671255 hasRelatedWork W3201166396 @default.
• W2896671255 hasRelatedWork W4200025849 @default.
• W2896671255 hasRelatedWork W4200140753 @default.
• W2896671255 hasRelatedWork W4220674352 @default.
• W2896671255 hasVolume "233" @default.

• next