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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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Sousa, Lc
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (5/5 displayed)
- 2005Eliminating forging defects using genetic algorithmscitations
- 2004Optimization of metal forming processescitations
- 2004Preform optimal design in metal forging using genetic algorithmscitations
- 2004Optimisation of shape and process parameters in metal forging using genetic algorithmscitations
- 2000A multilevel approach to optimization of bulk forming processes
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article
Eliminating forging defects using genetic algorithms
Abstract
In this article, an optimization method for metal forging process designs using finite element-based simulation is presented. Using as entry parameters the specifications of the final product the so-called inverse techniques developed for optimization problems allows the calculation of the optimal solution, the design parameters that produce the required product. An evolutionary genetic algorithm is proposed to calculate optimal shape geometry and temperature. An example demonstrating the efficiency of the developed method is presented considering a two-stage hot forging process. It considers optimization of the process parameters to reduce the difference between the realized and the prescribed final forged shape under minimal energy consumption, restricting the maximum temperature.