FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W244961340> ?p ?o ?g. }

• W244961340 endingPage "154" @default.
• W244961340 startingPage "144" @default.
• W244961340 abstract "For safety analysis of Nuclear Power Plants (NPPs), Best Estimate (BE) Thermal Hydraulic (TH) codes are used to predict system response in normal and accidental conditions. The assessment of the uncertainties of TH codes is a critical issue for system failure probability quantification. In this paper, we consider passive safety systems of advanced NPPs and present a novel approach of Sensitivity Analysis (SA). The approach is based on Finite Mixture Models (FMMs) to approximate the probability density function (i.e., the uncertainty) of the output of the passive safety system TH code with a limited number of simulations. We propose a novel Sensitivity Analysis (SA) method for keeping the computational cost low: an Expectation Maximization (EM) algorithm is used to calculate the saliency of the TH code input variables for identifying those that most affect the system functional failure. The novel approach is compared with a standard variance decomposition method on a case study considering a Passive Containment Cooling System (PCCS) of an Advanced Pressurized reactor AP1000." @default.
• W244961340 created "2016-06-24" @default.
• W244961340 creator A5007304896 @default.
• W244961340 creator A5026740851 @default.
• W244961340 creator A5062170722 @default.
• W244961340 creator A5070579143 @default.
• W244961340 date "2015-08-01" @default.
• W244961340 modified "2023-09-27" @default.
• W244961340 title "Finite mixture models for sensitivity analysis of thermal hydraulic codes for passive safety systems analysis" @default.
• W244961340 cites W1968762217 @default.
• W244961340 cites W1968766715 @default.
• W244961340 cites W1971445084 @default.
• W244961340 cites W1974828146 @default.
• W244961340 cites W1975535603 @default.
• W244961340 cites W2008359408 @default.
• W244961340 cites W2024011045 @default.
• W244961340 cites W2027956904 @default.
• W244961340 cites W2033136795 @default.
• W244961340 cites W2037243764 @default.
• W244961340 cites W2040435117 @default.
• W244961340 cites W2041837861 @default.
• W244961340 cites W2049774453 @default.
• W244961340 cites W2051882687 @default.
• W244961340 cites W2052531064 @default.
• W244961340 cites W2057004957 @default.
• W244961340 cites W2060436283 @default.
• W244961340 cites W2060935059 @default.
• W244961340 cites W2067582691 @default.
• W244961340 cites W2076205816 @default.
• W244961340 cites W2085360226 @default.
• W244961340 cites W2093469302 @default.
• W244961340 cites W2104270955 @default.
• W244961340 cites W2122121657 @default.
• W244961340 cites W2137214812 @default.
• W244961340 cites W2147102700 @default.
• W244961340 cites W2157255696 @default.
• W244961340 cites W2159703912 @default.
• W244961340 cites W2162526793 @default.
• W244961340 cites W2162692969 @default.
• W244961340 cites W65021417 @default.
• W244961340 doi "https://doi.org/10.1016/j.nucengdes.2015.04.035" @default.
• W244961340 hasPublicationYear "2015" @default.
• W244961340 type Work @default.
• W244961340 sameAs 244961340 @default.
• W244961340 citedByCount "13" @default.
• W244961340 countsByYear W2449613402015 @default.
• W244961340 countsByYear W2449613402016 @default.
• W244961340 countsByYear W2449613402017 @default.
• W244961340 countsByYear W2449613402018 @default.
• W244961340 countsByYear W2449613402020 @default.
• W244961340 countsByYear W2449613402021 @default.
• W244961340 crossrefType "journal-article" @default.
• W244961340 hasAuthorship W244961340A5007304896 @default.
• W244961340 hasAuthorship W244961340A5026740851 @default.
• W244961340 hasAuthorship W244961340A5062170722 @default.
• W244961340 hasAuthorship W244961340A5070579143 @default.
• W244961340 hasBestOaLocation W2449613402 @default.
• W244961340 hasConcept C121332964 @default.
• W244961340 hasConcept C126255220 @default.
• W244961340 hasConcept C127413603 @default.
• W244961340 hasConcept C14036430 @default.
• W244961340 hasConcept C174379495 @default.
• W244961340 hasConcept C177264268 @default.
• W244961340 hasConcept C177803969 @default.
• W244961340 hasConcept C185544564 @default.
• W244961340 hasConcept C199360897 @default.
• W244961340 hasConcept C200601418 @default.
• W244961340 hasConcept C21200559 @default.
• W244961340 hasConcept C24326235 @default.
• W244961340 hasConcept C2776330181 @default.
• W244961340 hasConcept C2776760102 @default.
• W244961340 hasConcept C2778917722 @default.
• W244961340 hasConcept C2779979336 @default.
• W244961340 hasConcept C33923547 @default.
• W244961340 hasConcept C41008148 @default.
• W244961340 hasConcept C44154836 @default.
• W244961340 hasConcept C50517652 @default.
• W244961340 hasConcept C78458016 @default.
• W244961340 hasConcept C78519656 @default.
• W244961340 hasConcept C86803240 @default.
• W244961340 hasConcept C91914117 @default.
• W244961340 hasConcept C97355855 @default.
• W244961340 hasConceptScore W244961340C121332964 @default.
• W244961340 hasConceptScore W244961340C126255220 @default.
• W244961340 hasConceptScore W244961340C127413603 @default.
• W244961340 hasConceptScore W244961340C14036430 @default.
• W244961340 hasConceptScore W244961340C174379495 @default.
• W244961340 hasConceptScore W244961340C177264268 @default.
• W244961340 hasConceptScore W244961340C177803969 @default.
• W244961340 hasConceptScore W244961340C185544564 @default.
• W244961340 hasConceptScore W244961340C199360897 @default.
• W244961340 hasConceptScore W244961340C200601418 @default.
• W244961340 hasConceptScore W244961340C21200559 @default.
• W244961340 hasConceptScore W244961340C24326235 @default.
• W244961340 hasConceptScore W244961340C2776330181 @default.
• W244961340 hasConceptScore W244961340C2776760102 @default.
• W244961340 hasConceptScore W244961340C2778917722 @default.
• W244961340 hasConceptScore W244961340C2779979336 @default.

• next