FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4379662125> ?p ?o ?g. }

• W4379662125 endingPage "824" @default.
• W4379662125 startingPage "812" @default.
• W4379662125 abstract "Due to its excellent performance, the self-piercing riveting (SPR) process has been widely used in auto body manufacturing in recent years. The need for efficient and reliable design of SPR process parameters is growing in industry. Traditional trial-and-error design methods rely on historical experience and can be limited by physical experimental materials and equipment. Data-driven methods rely on data accuracy and data volume, and data from a single source is often inadequate to meet design needs. To address these issues, a multi-fidelity data-driven optimization design framework is proposed in this paper. The most significant feature of this framework is the fusion of physical experiment data and simulation data to build surrogate models. In this framework, a modified optimal Latin hypercube sampling method and a multi-fidelity surrogate model based on transfer learning and neural networks are proposed for SPR process. This multi-fidelity surrogate model can use a very small amount of experiment data to modify the surrogate model built on simulation data based on transfer learning, so that the model predictions can more closely match the physical experiment results at a lower modeling cost. Benefit from this method, the proposed framework can balance the contradiction between design accuracy and development cost compared to a single-fidelity data-driven framework. The application cases show that the prediction errors of the multi-fidelity models are <0.1 mm for the key geometric parameters of the SPR joint. As verified by physical experiments, the rivets and dies selected by the framework are the optimal solutions within the optional range. To the authors' knowledge, this is the first time that a multi-fidelity modeling method has been introduced to the field of SPR process, to solve the process parameter optimization design problem. Further, the method is not limited to the use of SPR process but can be applied as a paradigm in other engineering optimization design problems, especially in joining process parameter design problems." @default.
• W4379662125 created "2023-06-08" @default.
• W4379662125 creator A5022792284 @default.
• W4379662125 creator A5031728253 @default.
• W4379662125 creator A5032614974 @default.
• W4379662125 creator A5034911046 @default.
• W4379662125 creator A5057471185 @default.
• W4379662125 creator A5071514657 @default.
• W4379662125 creator A5085346031 @default.
• W4379662125 date "2023-08-01" @default.
• W4379662125 modified "2023-09-25" @default.
• W4379662125 title "Multi-fidelity data-driven optimization design framework for self-piercing riveting process parameters" @default.
• W4379662125 cites W1977046327 @default.
• W4379662125 cites W2028717548 @default.
• W4379662125 cites W2061192441 @default.
• W4379662125 cites W2080293387 @default.
• W4379662125 cites W2118513056 @default.
• W4379662125 cites W2294323411 @default.
• W4379662125 cites W2421768884 @default.
• W4379662125 cites W2510279142 @default.
• W4379662125 cites W2515204417 @default.
• W4379662125 cites W2730506376 @default.
• W4379662125 cites W2735938873 @default.
• W4379662125 cites W2749552251 @default.
• W4379662125 cites W2808329891 @default.
• W4379662125 cites W2900477816 @default.
• W4379662125 cites W2929679623 @default.
• W4379662125 cites W2963241999 @default.
• W4379662125 cites W2984769126 @default.
• W4379662125 cites W3003568819 @default.
• W4379662125 cites W3007216765 @default.
• W4379662125 cites W3020964501 @default.
• W4379662125 cites W3098407580 @default.
• W4379662125 cites W3192516849 @default.
• W4379662125 cites W3216987970 @default.
• W4379662125 cites W4213050393 @default.
• W4379662125 cites W4221022185 @default.
• W4379662125 cites W4292869424 @default.
• W4379662125 cites W4293066998 @default.
• W4379662125 cites W4296661842 @default.
• W4379662125 doi "https://doi.org/10.1016/j.jmapro.2023.05.103" @default.
• W4379662125 hasPublicationYear "2023" @default.
• W4379662125 type Work @default.
• W4379662125 citedByCount "0" @default.
• W4379662125 crossrefType "journal-article" @default.
• W4379662125 hasAuthorship W4379662125A5022792284 @default.
• W4379662125 hasAuthorship W4379662125A5031728253 @default.
• W4379662125 hasAuthorship W4379662125A5032614974 @default.
• W4379662125 hasAuthorship W4379662125A5034911046 @default.
• W4379662125 hasAuthorship W4379662125A5057471185 @default.
• W4379662125 hasAuthorship W4379662125A5071514657 @default.
• W4379662125 hasAuthorship W4379662125A5085346031 @default.
• W4379662125 hasConcept C105795698 @default.
• W4379662125 hasConcept C111919701 @default.
• W4379662125 hasConcept C119857082 @default.
• W4379662125 hasConcept C124101348 @default.
• W4379662125 hasConcept C131675550 @default.
• W4379662125 hasConcept C13280743 @default.
• W4379662125 hasConcept C185798385 @default.
• W4379662125 hasConcept C19499675 @default.
• W4379662125 hasConcept C205649164 @default.
• W4379662125 hasConcept C20820323 @default.
• W4379662125 hasConcept C2776459999 @default.
• W4379662125 hasConcept C33923547 @default.
• W4379662125 hasConcept C34559072 @default.
• W4379662125 hasConcept C41008148 @default.
• W4379662125 hasConcept C55037315 @default.
• W4379662125 hasConcept C76155785 @default.
• W4379662125 hasConcept C98045186 @default.
• W4379662125 hasConceptScore W4379662125C105795698 @default.
• W4379662125 hasConceptScore W4379662125C111919701 @default.
• W4379662125 hasConceptScore W4379662125C119857082 @default.
• W4379662125 hasConceptScore W4379662125C124101348 @default.
• W4379662125 hasConceptScore W4379662125C131675550 @default.
• W4379662125 hasConceptScore W4379662125C13280743 @default.
• W4379662125 hasConceptScore W4379662125C185798385 @default.
• W4379662125 hasConceptScore W4379662125C19499675 @default.
• W4379662125 hasConceptScore W4379662125C205649164 @default.
• W4379662125 hasConceptScore W4379662125C20820323 @default.
• W4379662125 hasConceptScore W4379662125C2776459999 @default.
• W4379662125 hasConceptScore W4379662125C33923547 @default.
• W4379662125 hasConceptScore W4379662125C34559072 @default.
• W4379662125 hasConceptScore W4379662125C41008148 @default.
• W4379662125 hasConceptScore W4379662125C55037315 @default.
• W4379662125 hasConceptScore W4379662125C76155785 @default.
• W4379662125 hasConceptScore W4379662125C98045186 @default.
• W4379662125 hasLocation W43796621251 @default.
• W4379662125 hasOpenAccess W4379662125 @default.
• W4379662125 hasPrimaryLocation W43796621251 @default.
• W4379662125 hasRelatedWork W2081083659 @default.
• W4379662125 hasRelatedWork W2796351947 @default.
• W4379662125 hasRelatedWork W2889617176 @default.
• W4379662125 hasRelatedWork W2895946267 @default.
• W4379662125 hasRelatedWork W2995310634 @default.
• W4379662125 hasRelatedWork W3042131354 @default.
• W4379662125 hasRelatedWork W3210697285 @default.
• W4379662125 hasRelatedWork W4206227859 @default.
• W4379662125 hasRelatedWork W4379662125 @default.

• next