Abstract
Steel industrial engineers must estimate optimal operational parameters of industrial processes and the correct model for complex material behaviour. Common practice has been to base these determinations on classic techniques, such as tables and theoretical calculations. In this paper three successful experiences combining finite element modelling with genetic algorithms are reported. On the one hand, two cases of improvement in steel industrial processes are explained; on the other hand, the efficient determination of realistic material behaviour laws is presented. The proposed methodology optimizes and fully automates these determinations. The reliability and effectiveness of combining genetic algorithms and the finite element method is demonstrated in all cases.
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Sanz-García, A., Lostado-Lorza, R., Pernía-Espinoza, A., Martínez-de-Pisón-Ascacíbar, F.J. (2011). Improving Steel Industrial Processes Using Genetic Algorithms and Finite Element Method. In: Corchado, E., Snášel, V., Sedano, J., Hassanien, A.E., Calvo, J.L., Ślȩzak, D. (eds) Soft Computing Models in Industrial and Environmental Applications, 6th International Conference SOCO 2011. Advances in Intelligent and Soft Computing, vol 87. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19644-7_25
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DOI: https://doi.org/10.1007/978-3-642-19644-7_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19643-0
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