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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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Jahazi, Mohammad
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (17/17 displayed)
- 2025Kinetics of Austenite Formation in a Medium-Carbon, Low-Alloy Steel with an Initial Martensite Microstructure: Influence of Prior Austenite Grain Sizecitations
- 2023Interpolation and Extrapolation Performance Measurement of Analytical and ANN-Based Flow Laws for Hot Deformation Behavior of Medium Carbon Steelcitations
- 2023Interpolation and Extrapolation Performance Measurement of Analytical and ANN-Based Flow Laws for Hot Deformation Behavior of Medium Carbon Steelcitations
- 2023Influence of Oxygen Content in the Protective Gas on Pitting Corrosion Resistance of a 316L Stainless Steel Weld Jointcitations
- 2022Effect of heat treatments on microstructural and mechanical characteristics of dissimilar friction stir welded 2198/2024 aluminum alloyscitations
- 2022Effect of heat treatments on microstructural and mechanical characteristics of dissimilar friction stir welded 2198/2024 aluminum alloyscitations
- 2022Dissimilar linear friction welding of selective laser melted Inconel 718 to forged Ni-based superalloy AD730TM: evolution of strengthening phasescitations
- 2021Assessing the scale contributing factors of three carbide-free bainitic steels: A complementary theoretical and experimental approachcitations
- 2021Post-Weld Heat Treatment of Additively Manufactured Inconel 718 Welded to Forged Ni-Based Superalloy AD730 by Linear Friction Weldingcitations
- 2021Effect of heat treatments on microstructural and mechanical characteristics of dissimilar friction stir welded 2198/2024 aluminum alloyscitations
- 2020Microstructure Evolution of Selective Laser Melted Inconel 718: Influence of High Heating Ratescitations
- 2019Hot ductility behavior of AD730™ nickel-base superalloycitations
- 2018Effect of tool geometry and welding speed on mechanical properties of dissimilar AA2198–AA2024 FSWed jointcitations
- 2018Effect of tool geometry and welding speed on mechanical properties of dissimilar AA2198–AA2024 FSWed jointcitations
- 2016The Influence of Tool Geometry on Mechanical Properties of Friction Stir Welded AA-2024 and AA-2198 Joints
- 2016Friction stir welding of AA2024 and AA2198 Aluminum alloys: effect of tool geometry and process parameters
- 2009Effect of pre- and post-weld heat treatment on metallurgical and tensile properties of Inconel 718 alloy butt joints welded using 4 kW Nd:YAG lasercitations
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article
Interpolation and Extrapolation Performance Measurement of Analytical and ANN-Based Flow Laws for Hot Deformation Behavior of Medium Carbon Steel
Abstract
<jats:p>In the present work, a critical analysis of the most-commonly used analytical models and recently introduced ANN-based models was performed to evaluate their predictive accuracy within and outside the experimental interval used to generate them. The high-temperature deformation behavior of a medium carbon steel was studied over a wide range of strains, strain rates, and temperatures using hot compression tests on a Gleeble-3800. The experimental flow curves were modeled using the Johnson–Cook, Modified-Zerilli–Armstrong, Hansel–Spittel, Arrhenius, and PTM models, as well as an ANN model. The mean absolute relative error and root-mean-squared error values were used to quantify the predictive accuracy of the models analyzed. The results indicated that the Johnson–Cook and Modified-Zerilli–Armstrong models had a significant error, while the Hansel–Spittel, PTM, and Arrhenius models were able to predict the behavior of this alloy. The ANN model showed excellent agreement between the predicted and experimental flow curves, with an error of less than 0.62%. To validate the performance, the ability to interpolate and extrapolate the experimental data was also tested. The Hansel–Spittel, PTM, and Arrhenius models showed good interpolation and extrapolation capabilities. However, the ANN model was the most-powerful of all the models.</jats:p>