| 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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Solhjoo, Soheil
University of Groningen
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (7/7 displayed)
- 2021State of the art methods to post-process mechanical test data to characterize the hot deformation behavior of metalscitations
- 2020Effects of loading conditions on free surface roughening of AISI 420 martensitic stainless steelcitations
- 2017Two phenomenological models to predict the single peak flow stress curves up to the peak during hot deformationcitations
- 2014Determination of flow stress and the critical strain for the onset of dynamic recrystallization using a sine function
- 2014Two new mathematical models to predict the flow stress at hot deformation
- 2014Evaluation of coefficient of friction in bulk metal formingcitations
- 2013Characterization of nitrocarburized surface layer on AISI 1020 steel by electrolytic plasma processing in an urea electrolytecitations
Places of action
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article
Two phenomenological models to predict the single peak flow stress curves up to the peak during hot deformation
Abstract
Based on both linear and nonlinear estimations of work hardening rate versus strain curves, two mathematical models have been developed to predict the stress-strain curves under hot working conditions up to the peak stress. The models were validated for a mechanically alloyed Al6063/0.75Al2O3/0.75Y2O3 nanocomposite compressed under different hot forming conditions. The predicted results from both models are found to be in accord with the experimental flow stress curves up to the peak. For the present system, the linear model is found to more accurately predict the flow stress (with an average error of 0.81%) relative to the nonlinear model (with an average error of 2.06%).