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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Prajadhiana, Keval P.
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Publications (2/2 displayed)
- 2022Experimental validation of numerical simulation on deformation behaviour induced by wire arc additive manufacturing with feedstock SS316L on substrate S235citations
- 2022Numerical modelling and experimental analysis on angular strain induced by bead-on-plate SS316L GMAW using inherent strain and thermomechanical methodscitations
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article
Numerical modelling and experimental analysis on angular strain induced by bead-on-plate SS316L GMAW using inherent strain and thermomechanical methods
Abstract
<p>This study presents a basic investigation on angular strain behaviour of substrate using experiment and three different numerical computations based on elastic and elastic–plastic FEM methods. In simulation, a 3D simplified rectangular weld bead geometry was modelled and computed using general purposed numerical software MSC Marc/Mentat. While elastic FEM with well-known inherent strain method-user defined (ISM-UD) and new ISM weld-kinematics (ISM-WK) were applied in which the inherent strain values were empirically estimated with regard to process parameters, physical properties, and effective area on heat affected zone, the most popular elastic–plastic or thermo-mechanical method (TMM) considers temperature-dependent isotropic hardening rule and heat source model. For verification purpose, experimental analysis was conducted as bead-on-plate process with austenitic stainless steel material SS316L using GMAW robotic welding. It can be concluded that TMM can predict the total experimental angular strain with mean percentage error up to ca. 7% compared to ISM with 19% for weld kinematics and 29% for user defined. In terms of computational time, ISM gave higher potential to be implemented with only 10% of TMM.</p>