期刊
COMPUTATIONAL MATERIALS SCIENCE
卷 50, 期 8, 页码 2502-2516出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.commatsci.2011.03.034
关键词
Fe-Zn system; Hot dip galvanization; Coating; Molecular Dynamics; Optimization; Neural network; Genetic Algorithms; Multi-objective optimization; Evolutionary algorithm; Pareto frontier
资金
- TATA Steel
Various interfaces in Zn coated steel are examined for their stability on the basis of two conflicting requirements of minimum deformation at a maximum absorption of shear energy. The shearing process is simulated using a Molecular Dynamics technique and meta-models of both energy and strain are constructed using an Evolutionary Neural Network that itself evolved through a multi-objective Genetic Algorithm. Simultaneous optimization of deformation and energy absorption is conducted with a Predator-prey Genetic Algorithm and the resulting Pareto frontiers are analyzed and discussed. The findings show good correspondence with existing experimental observations. (C) 2011 Elsevier B.V. All rights reserved.
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