| 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
Thermo-chemical-mechanical simulation of low temperature nitriding of austenitic stainless steel; inverse modelling of surface reaction rates
Abstract
A multi-physics thermo-chemical-mechanical 1-dimensional implicit finite difference model is presented to simulate the evolution of composition and residual stress profiles over the expanded austenite case developing during low temperature nitriding of austenitic stainless steels. The model combines 1-dimensional diffusion of nitrogen in the depth direction with a concentration-dependent diffusivity, elasto-plastic accommodation of the lattice expansion, stress gradient-induced diffusion of nitrogen, solid solution-strengthening by nitrogen and trapping of nitrogen by chromium atoms. The rate of the surface reaction governing the transfer of nitrogen from the gas to the solid is unknown and was evaluated by inverse modelling. The modelling was applied adopting the surface reaction rate as the only fitting parameter and taking mass-uptake curves (thermogravimetry) as the constraint, while all other data were taken from established literature values. Very good agreement is achieved between the predicted and experimental composition-depth profiles. Further, the applicability of the present model to plasma nitriding was verified by simulating (not fitting) the evolution of composition-depth profiles obtained after plasma nitriding of stainless steel. The good to very good agreement of the present model's predictions with experimental data for gaseous and plasma nitriding, indicates that the essential multi-physics influences and parameters are taken into account, with a minimum of adjustable parameters.