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Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes

The use of Finite Element (FE) simulation software to adequately predict the outcome of sheet metal forming processes is crucial to enhancing the efficiency and lowering the development time of such processes, whilst reducing costs involved in trial-and-error prototyping. Recent focus on the substit...

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Autores principales: Zhou, Du, Yuan, Xi, Gao, Haoxiang, Wang, Ailing, Liu, Jun, El Fakir, Omer, Politis, Denis J., Wang, Liliang, Lin, Jianguo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MyJove Corporation 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5226393/
https://www.ncbi.nlm.nih.gov/pubmed/28060298
http://dx.doi.org/10.3791/53957
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author Zhou, Du
Yuan, Xi
Gao, Haoxiang
Wang, Ailing
Liu, Jun
El Fakir, Omer
Politis, Denis J.
Wang, Liliang
Lin, Jianguo
author_facet Zhou, Du
Yuan, Xi
Gao, Haoxiang
Wang, Ailing
Liu, Jun
El Fakir, Omer
Politis, Denis J.
Wang, Liliang
Lin, Jianguo
author_sort Zhou, Du
collection PubMed
description The use of Finite Element (FE) simulation software to adequately predict the outcome of sheet metal forming processes is crucial to enhancing the efficiency and lowering the development time of such processes, whilst reducing costs involved in trial-and-error prototyping. Recent focus on the substitution of steel components with aluminum alloy alternatives in the automotive and aerospace sectors has increased the need to simulate the forming behavior of such alloys for ever more complex component geometries. However these alloys, and in particular their high strength variants, exhibit limited formability at room temperature, and high temperature manufacturing technologies have been developed to form them. Consequently, advanced constitutive models are required to reflect the associated temperature and strain rate effects. Simulating such behavior is computationally very expensive using conventional FE simulation techniques. This paper presents a novel Knowledge Based Cloud FE (KBC-FE) simulation technique that combines advanced material and friction models with conventional FE simulations in an efficient manner thus enhancing the capability of commercial simulation software packages. The application of these methods is demonstrated through two example case studies, namely: the prediction of a material's forming limit under hot stamping conditions, and the tool life prediction under multi-cycle loading conditions.
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spelling pubmed-52263932017-01-26 Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes Zhou, Du Yuan, Xi Gao, Haoxiang Wang, Ailing Liu, Jun El Fakir, Omer Politis, Denis J. Wang, Liliang Lin, Jianguo J Vis Exp Engineering The use of Finite Element (FE) simulation software to adequately predict the outcome of sheet metal forming processes is crucial to enhancing the efficiency and lowering the development time of such processes, whilst reducing costs involved in trial-and-error prototyping. Recent focus on the substitution of steel components with aluminum alloy alternatives in the automotive and aerospace sectors has increased the need to simulate the forming behavior of such alloys for ever more complex component geometries. However these alloys, and in particular their high strength variants, exhibit limited formability at room temperature, and high temperature manufacturing technologies have been developed to form them. Consequently, advanced constitutive models are required to reflect the associated temperature and strain rate effects. Simulating such behavior is computationally very expensive using conventional FE simulation techniques. This paper presents a novel Knowledge Based Cloud FE (KBC-FE) simulation technique that combines advanced material and friction models with conventional FE simulations in an efficient manner thus enhancing the capability of commercial simulation software packages. The application of these methods is demonstrated through two example case studies, namely: the prediction of a material's forming limit under hot stamping conditions, and the tool life prediction under multi-cycle loading conditions. MyJove Corporation 2016-12-13 /pmc/articles/PMC5226393/ /pubmed/28060298 http://dx.doi.org/10.3791/53957 Text en Copyright © 2016, Journal of Visualized Experiments http://creativecommons.org/licenses/by/3.0/us/ This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 License. To view a copy of this license, visithttp://creativecommons.org/licenses/by/3.0/us/
spellingShingle Engineering
Zhou, Du
Yuan, Xi
Gao, Haoxiang
Wang, Ailing
Liu, Jun
El Fakir, Omer
Politis, Denis J.
Wang, Liliang
Lin, Jianguo
Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
title Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
title_full Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
title_fullStr Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
title_full_unstemmed Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
title_short Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
title_sort knowledge based cloud fe simulation of sheet metal forming processes
topic Engineering
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5226393/
https://www.ncbi.nlm.nih.gov/pubmed/28060298
http://dx.doi.org/10.3791/53957
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