FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4221034671> ?p ?o ?g. }

• W4221034671 endingPage "e01045" @default.
• W4221034671 startingPage "e01045" @default.
• W4221034671 abstract "This study aims to predict the accurate stress intensity factor (SIF) of a crack propagating in offshore piping, which is one of the crucial factors used to assess the remaining fatigue life (RFL) of offshore pipelines. Four soft computing techniques are examined and evaluated in the modeling of SIF of a crack propagating in topside piping, as an inexpensive alternative to the finite element methods (FEM). In the training and testing stages, developed models of Functional Network (FN), Emotional Neural Network (ENN), Relevance Vector Machine (RVM), and minimax probability machine regression (MPMR) for SIF prediction were used and compared. Also, a comparative study was conducted for the developed models with the Adaptive Gaussian Process Regression Model (AGPRM). The load, crack depth, and half crack length have been adopted as input variables of the models, and the output variable is the SIF. All variables were simulated and determined based on the flat-plate FEM model. The analysis confirms that the RVM and MPMR models are superior to FN and ENN models for SIF prediction in the training and testing stages. In addition, the RVM and MPMR models show better than AGPRM for the prediction of pipe SIF in the testing stage. The MPMR accurately outperforms all models within 1.31% prediction error, and the majority of its error values at 99% confidence level fall within ±29.64 MPamm." @default.
• W4221034671 created "2022-04-03" @default.
• W4221034671 creator A5004350213 @default.
• W4221034671 creator A5031947697 @default.
• W4221034671 creator A5063113402 @default.
• W4221034671 creator A5076836354 @default.
• W4221034671 creator A5083620416 @default.
• W4221034671 date "2022-06-01" @default.
• W4221034671 modified "2023-09-26" @default.
• W4221034671 title "Stress intensity factor prediction on offshore pipelines using surrogate modeling techniques" @default.
• W4221034671 cites W1974528911 @default.
• W4221034671 cites W1985479415 @default.
• W4221034671 cites W1990979046 @default.
• W4221034671 cites W2001036584 @default.
• W4221034671 cites W2013488777 @default.
• W4221034671 cites W2021615327 @default.
• W4221034671 cites W2033303770 @default.
• W4221034671 cites W2047863323 @default.
• W4221034671 cites W2052798212 @default.
• W4221034671 cites W2058721856 @default.
• W4221034671 cites W2062136408 @default.
• W4221034671 cites W2078175064 @default.
• W4221034671 cites W2090282705 @default.
• W4221034671 cites W2091474959 @default.
• W4221034671 cites W2100245841 @default.
• W4221034671 cites W2119118554 @default.
• W4221034671 cites W2293852783 @default.
• W4221034671 cites W2331015670 @default.
• W4221034671 cites W2550265600 @default.
• W4221034671 cites W2555427010 @default.
• W4221034671 cites W2584996213 @default.
• W4221034671 cites W2587493242 @default.
• W4221034671 cites W2613566696 @default.
• W4221034671 cites W2667628605 @default.
• W4221034671 cites W2735749589 @default.
• W4221034671 cites W2737026183 @default.
• W4221034671 cites W2763466511 @default.
• W4221034671 cites W2766002319 @default.
• W4221034671 cites W2800264110 @default.
• W4221034671 cites W2889474332 @default.
• W4221034671 cites W2891482175 @default.
• W4221034671 cites W2896575739 @default.
• W4221034671 cites W2900056092 @default.
• W4221034671 cites W2914493787 @default.
• W4221034671 cites W2963265946 @default.
• W4221034671 cites W2964938317 @default.
• W4221034671 cites W2967114421 @default.
• W4221034671 cites W2977816628 @default.
• W4221034671 cites W2987048143 @default.
• W4221034671 cites W3092179965 @default.
• W4221034671 cites W3215546032 @default.
• W4221034671 cites W79814905 @default.
• W4221034671 doi "https://doi.org/10.1016/j.cscm.2022.e01045" @default.
• W4221034671 hasPublicationYear "2022" @default.
• W4221034671 type Work @default.
• W4221034671 citedByCount "1" @default.
• W4221034671 countsByYear W42210346712023 @default.
• W4221034671 crossrefType "journal-article" @default.
• W4221034671 hasAuthorship W4221034671A5004350213 @default.
• W4221034671 hasAuthorship W4221034671A5031947697 @default.
• W4221034671 hasAuthorship W4221034671A5063113402 @default.
• W4221034671 hasAuthorship W4221034671A5076836354 @default.
• W4221034671 hasAuthorship W4221034671A5083620416 @default.
• W4221034671 hasBestOaLocation W42210346711 @default.
• W4221034671 hasConcept C119857082 @default.
• W4221034671 hasConcept C121332964 @default.
• W4221034671 hasConcept C127413603 @default.
• W4221034671 hasConcept C135628077 @default.
• W4221034671 hasConcept C152877465 @default.
• W4221034671 hasConcept C163716315 @default.
• W4221034671 hasConcept C2779095084 @default.
• W4221034671 hasConcept C41008148 @default.
• W4221034671 hasConcept C50644808 @default.
• W4221034671 hasConcept C54303661 @default.
• W4221034671 hasConcept C61326573 @default.
• W4221034671 hasConcept C62520636 @default.
• W4221034671 hasConcept C66938386 @default.
• W4221034671 hasConcept C78519656 @default.
• W4221034671 hasConceptScore W4221034671C119857082 @default.
• W4221034671 hasConceptScore W4221034671C121332964 @default.
• W4221034671 hasConceptScore W4221034671C127413603 @default.
• W4221034671 hasConceptScore W4221034671C135628077 @default.
• W4221034671 hasConceptScore W4221034671C152877465 @default.
• W4221034671 hasConceptScore W4221034671C163716315 @default.
• W4221034671 hasConceptScore W4221034671C2779095084 @default.
• W4221034671 hasConceptScore W4221034671C41008148 @default.
• W4221034671 hasConceptScore W4221034671C50644808 @default.
• W4221034671 hasConceptScore W4221034671C54303661 @default.
• W4221034671 hasConceptScore W4221034671C61326573 @default.
• W4221034671 hasConceptScore W4221034671C62520636 @default.
• W4221034671 hasConceptScore W4221034671C66938386 @default.
• W4221034671 hasConceptScore W4221034671C78519656 @default.
• W4221034671 hasLocation W42210346711 @default.
• W4221034671 hasOpenAccess W4221034671 @default.
• W4221034671 hasPrimaryLocation W42210346711 @default.
• W4221034671 hasRelatedWork W2023630867 @default.
• W4221034671 hasRelatedWork W2057388552 @default.
• W4221034671 hasRelatedWork W2350032752 @default.

• next