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Numerical modeling and failure prediction of laser welded joints in a support of car seat

Abstract : Nowadays environmental policies have become more strict towards the automotive industry to reduce the CO2 emission, therefore lightweight structures using high strength materials have become of great interest. Two different FE models namely “Solid Refine Model” (SRM) and “Shell Coarse Model” (SCM) have been developed and are being used as standard models by Faurecia Automotive Seating (Caligny). The SRM is capable to predict accurately the local welding behavior but unfortunately, due to its high computational cost, the SRM is not suitable for a full car seat modeling. On the other hand, the SCM is computationally efficient but it cannot predict the weld line behaviour. The aim of the present thesis is to develop a multimaterial FE model within the Ls-dyna commercial software, which will enhance the SCM to allow the accurate prediction of weld line behavior until failure with a reasonable computational cost. The standard quadrilateral shell FE is developed and enriched using a recently developed method called the “Interpolation Covers Method” (ICM) to capture the solution gradients accurately without mesh refinement. An elasto-plastic material model is developed within Ls-dyna commercial software which takes into account two different materials namely BM and HAZ inside a single shell element. The Generalized Incremental Stress State dependent damage Model has been implemented as a UMAT within Ls-dyna commercial software to predict the weld line failure in SCM. The different developments have allowed the SCM to become able to predict the complex behavior of the welded line accurately until failure, at low computational cost compatible with the industrial needs.
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Submitted on : Tuesday, November 14, 2017 - 9:31:17 PM
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  • HAL Id : tel-01635238, version 1

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Waseem Arif. Numerical modeling and failure prediction of laser welded joints in a support of car seat. Structural mechanics [physics.class-ph]. Université de Valenciennes et du Hainaut-Cambresis, 2017. English. ⟨NNT : 2017VALE0001⟩. ⟨tel-01635238⟩

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