| People | Locations | Statistics |
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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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Sonne, Mads S.
Technical University of Denmark
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (19/19 displayed)
- 2020Thermo-chemical-mechanical simulation of low temperature nitriding of austenitic stainless steel; inverse modelling of surface reaction ratescitations
- 2019A Characterization Study Relating Cross-Sectional Distribution of Fiber Volume Fraction and Permeability
- 2019Numerical Modelling of Heat Transfer using the 3D-ADI-DG Method - with Application for Pultrusion.
- 2019Fiber segmentation from 3D X-ray computed tomography of composites with continuous textured glass fibre yarns
- 2018Multiphysics modelling of manufacturing processes: A reviewcitations
- 2018Numerical Modelling of Mechanical Anisotropy during Low Temperature Nitriding of Stainless Steel
- 2018Uncovering the local inelastic interactions during manufacture of ductile cast iron: How the substructure of the graphite particles can induce residual stress concentrations in the matrixcitations
- 2018Thermomechanical Modelling of Direct-Drive Friction Welding Applying a Thermal Pseudo Mechanical Model for the Generation of Heatcitations
- 2017A FEM based methodology to simulate multiple crack propagation in friction stir weldscitations
- 2017Integrated Computational Modelling of Thermochemical Surface Engineering of Stainless Steel
- 2016Improvement in Surface Characterisitcs of Polymers for Subsequent Electroless Plating Using Liquid Assisted Laser Processingcitations
- 2016Free-form nanostructured tools for plastic injection moulding
- 2016Determination of stamp deformation during imprinting on semi-spherical surfaces
- 2016Multiple Crack Growth Prediction in AA2024-T3 Friction Stir Welded Joints, Including Manufacturing Effectscitations
- 2015Defining Allowable Physical Property Variations for High Accurate Measurements on Polymer Parts.citations
- 2015Modelling residual stresses in friction stir welding of Al alloys - a review of possibilities and future trendscitations
- 2015Comparison of residual stresses in sand- and chill casting of ductile cast iron wind turbine main shaftscitations
- 2015Modelling the residual stresses and microstructural evolution in Friction Stir Welding of AA2024-T3 including the Wagner-Kampmann precipitation model
- 2013The effect of hardening laws and thermal softening on modeling residual stresses in FSW of aluminum alloy 2024-T3citations
Places of action
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article
Multiple Crack Growth Prediction in AA2024-T3 Friction Stir Welded Joints, Including Manufacturing Effects
Abstract
A great deal of attention is currently paid by several industries toward the friction stir welding process to realize lightweight structures. Within this aim, the realistic prediction of fatigue behavior of welded assemblies is a key factor. In this work an integrated finite element method - dual boundary element method (FEM-DBEM) procedure, coupling the welding process simulation to the subsequent crack growth assessment, is proposed and applied to simulate multiple crack propagation, with allowance for manufacturing effects. The friction stir butt welding process of the precipitation hardened AA2024-T3 alloy was simulated using a thermo-mechanical FEM model to predict the process induced residual stress field and material softening. The computed stress field was transferred to a DBEM environment and superimposed to the stress field produced by a remote fatigue traction load applied on a notched specimen. The whole procedure was finally tested comparing simulation outcomes with experimental data. The good agreement obtained highlights the predictive capability of the method. The influence of the residual stress distribution on crack growth and the mutual interaction between propagating cracks were analyzed as well.