FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2054143721> ?p ?o ?g. }

• W2054143721 endingPage "7" @default.
• W2054143721 startingPage "1" @default.
• W2054143721 abstract "This research work highlights the use of artificial neural networks (ANN) for modelling the rate-dependent response of adhesive materials with the purpose of expanding the established method for modelling the response of adhesively bonded structures, and in particular single lap joints. The motivation for this work comes after a viscoplastic model developed in a previous research work failed to predict the response of single lap joints bonded with a rate dependent adhesive material. The viscoplastic model, however, was successful in replicating both bulk and shear properties of the used adhesive system. Predictions made using the rate-dependent von Mises material model proved to be successful in predicting the behaviour of single lap joints, but it could not model the shear data using the tensile data due to hydrostatic stress sensitivity in the adhesive itself. Accurate predictions of the rate-dependent behaviour using artificial neural networks are possible with the availability of stress and strain data sets from experiments. This is where the neural network constitutive model directly acquires the information on the material behaviour from experimental data sets. Material data defining both the tensile and shear response of the adhesive system was extracted from previous research work. An artificial neural network constitutive model was developed and then used to replicate experimental data and also to generate further data at other strain rates. The available model could be slightly modified and then used to investigate various geometrical parameters, such as overlap length, plate thickness and adhesive thickness on joint strength." @default.
• W2054143721 created "2016-06-24" @default.
• W2054143721 creator A5025218425 @default.
• W2054143721 date "2012-07-01" @default.
• W2054143721 modified "2023-09-29" @default.
• W2054143721 title "Use of artificial neural networks for modelling rate dependent behaviour of adhesive materials" @default.
• W2054143721 cites W1968865709 @default.
• W2054143721 cites W1974990239 @default.
• W2054143721 cites W2004320657 @default.
• W2054143721 cites W2006261727 @default.
• W2054143721 cites W2016236937 @default.
• W2054143721 cites W2021958191 @default.
• W2054143721 cites W2026545494 @default.
• W2054143721 cites W2038572147 @default.
• W2054143721 cites W2065928586 @default.
• W2054143721 cites W2082507048 @default.
• W2054143721 cites W2119907292 @default.
• W2054143721 cites W2140845925 @default.
• W2054143721 cites W2527319573 @default.
• W2054143721 doi "https://doi.org/10.1016/j.ijadhadh.2012.03.003" @default.
• W2054143721 hasPublicationYear "2012" @default.
• W2054143721 type Work @default.
• W2054143721 sameAs 2054143721 @default.
• W2054143721 citedByCount "13" @default.
• W2054143721 countsByYear W20541437212013 @default.
• W2054143721 countsByYear W20541437212015 @default.
• W2054143721 countsByYear W20541437212016 @default.
• W2054143721 countsByYear W20541437212019 @default.
• W2054143721 countsByYear W20541437212020 @default.
• W2054143721 countsByYear W20541437212021 @default.
• W2054143721 countsByYear W20541437212022 @default.
• W2054143721 countsByYear W20541437212023 @default.
• W2054143721 crossrefType "journal-article" @default.
• W2054143721 hasAuthorship W2054143721A5025218425 @default.
• W2054143721 hasConcept C100944820 @default.
• W2054143721 hasConcept C105795698 @default.
• W2054143721 hasConcept C112950240 @default.
• W2054143721 hasConcept C121332964 @default.
• W2054143721 hasConcept C127413603 @default.
• W2054143721 hasConcept C134853933 @default.
• W2054143721 hasConcept C135628077 @default.
• W2054143721 hasConcept C149342994 @default.
• W2054143721 hasConcept C154945302 @default.
• W2054143721 hasConcept C155165730 @default.
• W2054143721 hasConcept C159985019 @default.
• W2054143721 hasConcept C18762648 @default.
• W2054143721 hasConcept C192562407 @default.
• W2054143721 hasConcept C202973686 @default.
• W2054143721 hasConcept C2779227376 @default.
• W2054143721 hasConcept C33923547 @default.
• W2054143721 hasConcept C41008148 @default.
• W2054143721 hasConcept C50644808 @default.
• W2054143721 hasConcept C55037315 @default.
• W2054143721 hasConcept C55359492 @default.
• W2054143721 hasConcept C62520636 @default.
• W2054143721 hasConcept C66938386 @default.
• W2054143721 hasConcept C68928338 @default.
• W2054143721 hasConcept C78519656 @default.
• W2054143721 hasConcept C96035792 @default.
• W2054143721 hasConceptScore W2054143721C100944820 @default.
• W2054143721 hasConceptScore W2054143721C105795698 @default.
• W2054143721 hasConceptScore W2054143721C112950240 @default.
• W2054143721 hasConceptScore W2054143721C121332964 @default.
• W2054143721 hasConceptScore W2054143721C127413603 @default.
• W2054143721 hasConceptScore W2054143721C134853933 @default.
• W2054143721 hasConceptScore W2054143721C135628077 @default.
• W2054143721 hasConceptScore W2054143721C149342994 @default.
• W2054143721 hasConceptScore W2054143721C154945302 @default.
• W2054143721 hasConceptScore W2054143721C155165730 @default.
• W2054143721 hasConceptScore W2054143721C159985019 @default.
• W2054143721 hasConceptScore W2054143721C18762648 @default.
• W2054143721 hasConceptScore W2054143721C192562407 @default.
• W2054143721 hasConceptScore W2054143721C202973686 @default.
• W2054143721 hasConceptScore W2054143721C2779227376 @default.
• W2054143721 hasConceptScore W2054143721C33923547 @default.
• W2054143721 hasConceptScore W2054143721C41008148 @default.
• W2054143721 hasConceptScore W2054143721C50644808 @default.
• W2054143721 hasConceptScore W2054143721C55037315 @default.
• W2054143721 hasConceptScore W2054143721C55359492 @default.
• W2054143721 hasConceptScore W2054143721C62520636 @default.
• W2054143721 hasConceptScore W2054143721C66938386 @default.
• W2054143721 hasConceptScore W2054143721C68928338 @default.
• W2054143721 hasConceptScore W2054143721C78519656 @default.
• W2054143721 hasConceptScore W2054143721C96035792 @default.
• W2054143721 hasLocation W20541437211 @default.
• W2054143721 hasOpenAccess W2054143721 @default.
• W2054143721 hasPrimaryLocation W20541437211 @default.
• W2054143721 hasRelatedWork W103328049 @default.
• W2054143721 hasRelatedWork W2000912582 @default.
• W2054143721 hasRelatedWork W2089085266 @default.
• W2054143721 hasRelatedWork W2375968602 @default.
• W2054143721 hasRelatedWork W2729932191 @default.
• W2054143721 hasRelatedWork W2754169677 @default.
• W2054143721 hasRelatedWork W2795554382 @default.
• W2054143721 hasRelatedWork W2949583247 @default.
• W2054143721 hasRelatedWork W4250895611 @default.
• W2054143721 hasRelatedWork W4308359125 @default.
• W2054143721 hasVolume "36" @default.

• next