Matches in SemOpenAlex for { <https://semopenalex.org/work/W4310836124> ?p ?o ?g. }
- W4310836124 endingPage "105758" @default.
- W4310836124 startingPage "105758" @default.
- W4310836124 abstract "Extensive changes in the legal, commercial and technical requirements in engineering fields have necessitated automated real-time structural health monitoring (SHM) and instantaneous verification. An integrated system with mechanoluminescence (ML) and dual artificial intelligence (AI) modules with subsidiary finite element method (FEM) simulation is designed for in situ SHM and instantaneous verification. The ML module detects the exact position of a crack tip and evaluates the significance of existing cracks with a plastic stress-intensity factor (PSIF; KP ). ML fields and their corresponding KpML values are referenced and verified using the FEM simulation and bidirectional generative adversarial network (GAN). Well-trained forward and backward GANs create fake FEM and ML images that appear authentic to observers; a convolutional neural network is used to postulate precise PSIFs from fake images. Finally, the reliability of the proposed system to satisfy existing commercial requirements is validated in terms of tension, compact tension, AI, and instrumentation." @default.
- W4310836124 created "2022-12-19" @default.
- W4310836124 creator A5003749032 @default.
- W4310836124 creator A5033246805 @default.
- W4310836124 creator A5033516194 @default.
- W4310836124 creator A5040025378 @default.
- W4310836124 creator A5040417473 @default.
- W4310836124 creator A5053502119 @default.
- W4310836124 creator A5058741933 @default.
- W4310836124 creator A5083387138 @default.
- W4310836124 creator A5090743227 @default.
- W4310836124 date "2023-01-01" @default.
- W4310836124 modified "2023-10-16" @default.
- W4310836124 title "In situ health monitoring of multiscale structures and its instantaneous verification using mechanoluminescence and dual machine learning" @default.
- W4310836124 cites W1892204351 @default.
- W4310836124 cites W1979374986 @default.
- W4310836124 cites W1985824680 @default.
- W4310836124 cites W2019271732 @default.
- W4310836124 cites W2024154118 @default.
- W4310836124 cites W2028801673 @default.
- W4310836124 cites W2042338336 @default.
- W4310836124 cites W2047655099 @default.
- W4310836124 cites W2059136964 @default.
- W4310836124 cites W2066465134 @default.
- W4310836124 cites W2066539664 @default.
- W4310836124 cites W2077879311 @default.
- W4310836124 cites W2088192769 @default.
- W4310836124 cites W2144354855 @default.
- W4310836124 cites W2166753362 @default.
- W4310836124 cites W2257979135 @default.
- W4310836124 cites W2306570595 @default.
- W4310836124 cites W2514668410 @default.
- W4310836124 cites W2527189750 @default.
- W4310836124 cites W2554635793 @default.
- W4310836124 cites W2588612844 @default.
- W4310836124 cites W2594093994 @default.
- W4310836124 cites W2606596544 @default.
- W4310836124 cites W2618530766 @default.
- W4310836124 cites W2780546514 @default.
- W4310836124 cites W2790981088 @default.
- W4310836124 cites W2793605784 @default.
- W4310836124 cites W2805720635 @default.
- W4310836124 cites W2904775716 @default.
- W4310836124 cites W2911606041 @default.
- W4310836124 cites W2922854992 @default.
- W4310836124 cites W3096831136 @default.
- W4310836124 cites W3120076521 @default.
- W4310836124 cites W3174788865 @default.
- W4310836124 cites W3195360122 @default.
- W4310836124 cites W3199222954 @default.
- W4310836124 cites W4212812744 @default.
- W4310836124 cites W4221034033 @default.
- W4310836124 cites W4283310701 @default.
- W4310836124 cites W4284885689 @default.
- W4310836124 cites W64939638 @default.
- W4310836124 doi "https://doi.org/10.1016/j.isci.2022.105758" @default.
- W4310836124 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36590175" @default.
- W4310836124 hasPublicationYear "2023" @default.
- W4310836124 type Work @default.
- W4310836124 citedByCount "2" @default.
- W4310836124 countsByYear W43108361242023 @default.
- W4310836124 crossrefType "journal-article" @default.
- W4310836124 hasAuthorship W4310836124A5003749032 @default.
- W4310836124 hasAuthorship W4310836124A5033246805 @default.
- W4310836124 hasAuthorship W4310836124A5033516194 @default.
- W4310836124 hasAuthorship W4310836124A5040025378 @default.
- W4310836124 hasAuthorship W4310836124A5040417473 @default.
- W4310836124 hasAuthorship W4310836124A5053502119 @default.
- W4310836124 hasAuthorship W4310836124A5058741933 @default.
- W4310836124 hasAuthorship W4310836124A5083387138 @default.
- W4310836124 hasAuthorship W4310836124A5090743227 @default.
- W4310836124 hasBestOaLocation W43108361241 @default.
- W4310836124 hasConcept C111919701 @default.
- W4310836124 hasConcept C112950240 @default.
- W4310836124 hasConcept C118530786 @default.
- W4310836124 hasConcept C120665830 @default.
- W4310836124 hasConcept C121332964 @default.
- W4310836124 hasConcept C124952713 @default.
- W4310836124 hasConcept C127413603 @default.
- W4310836124 hasConcept C128996297 @default.
- W4310836124 hasConcept C135628077 @default.
- W4310836124 hasConcept C142362112 @default.
- W4310836124 hasConcept C148869448 @default.
- W4310836124 hasConcept C154945302 @default.
- W4310836124 hasConcept C163258240 @default.
- W4310836124 hasConcept C186068551 @default.
- W4310836124 hasConcept C191897082 @default.
- W4310836124 hasConcept C192562407 @default.
- W4310836124 hasConcept C2776247918 @default.
- W4310836124 hasConcept C2780980858 @default.
- W4310836124 hasConcept C41008148 @default.
- W4310836124 hasConcept C43214815 @default.
- W4310836124 hasConcept C50644808 @default.
- W4310836124 hasConcept C62520636 @default.
- W4310836124 hasConcept C66938386 @default.
- W4310836124 hasConcept C81363708 @default.
- W4310836124 hasConceptScore W4310836124C111919701 @default.
- W4310836124 hasConceptScore W4310836124C112950240 @default.