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analysis of deep drawing process to predict the forming severity considering inverse finite element and extended strain-based forming limit diagram
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نویسنده
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bostan shirin mehdi ,hashemi ramin ,assempour ahmad
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منبع
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journal of computational and applied research in mechanical engineering - 2018 - دوره : 8 - شماره : 1 - صفحه:39 -48
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چکیده
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An enhanced unfolding inverse finite element method (ifem) is used together with an extended strain-based forming limit diagram (efld) to develop a fast and reliable approach to predict the feasibility of the deep drawing process of a part and determining where the failure or defects can occur. in the developed unfolding ifem, the meshed part is properly fold out on the flat sheet and treated as a 2d problem to reduce the computation time. the large deformation relations, nonlinear material behavior and friction conditions in the blank holder zone are also considered to improve the accuracy and capability of the proposed ifem. the extended strain-based forming limit diagram based on the marciniak and kuczynski (m-k) model is computed and used to predict the onset of necking during sheet processing. the efld is built based on equivalent plastic strains and material flow direction at the end of forming. this new forming limit diagram is much less strain path dependent than the conventional forming limit diagram. furthermore, the use and interpretation of this new diagram are easier than the stress-based forming limit diagram. finally, two applied examples are presented to demonstrate the capability of the proposed approach.
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کلیدواژه
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sheet metal forming ,inverse finite element method ,strain path ,blank shape ,nonlinear deformation ,extended strain-based forming limit diagram
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آدرس
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amir kabir university of technology, school of biomedical engineering, ایران, iran university of science and technology, school of mechanical engineering, ایران, sharif university of technology, center of excellence in design, robotics and automation, department of mechanical engineering, ایران
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پست الکترونیکی
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assem@sharif.edu
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Authors
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