A computational intelligence based dislocation recognition during molecular dynamics simulation

Jianfeng Huang, D. Mcglinchey, Yuanxin Luo, Yi Chen
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引用次数: 1

Abstract

Dislocation evolution in metal is the majority response of external stress or strain during the deformation. In this paper, a computational intelligence aided dislocation recognition algorithm which is integrated in a molecular dynamics simulation is proposed. This algorithm is inspired by genetic algorithm(GA) and follows the main GA process in which the initial population is the disperse nodes set and is under the select, crossover to evolve the new generation of nodes set. Finally, two examples of the dislocation recognition during fatigue simulation by using this algorithm is provided with good result when comparing with the traditional MD post process method.
分子动力学模拟中基于计算智能的位错识别
变形过程中,金属的位错演化是外部应力或应变的主要响应。本文提出了一种结合分子动力学模拟的计算智能辅助位错识别算法。该算法受遗传算法(GA)的启发,遵循遗传算法的主要过程,即初始种群为分散节点集,在选择、交叉下进化新一代节点集。最后,将该算法应用于疲劳仿真中的两个错位识别实例,与传统的MD后处理方法进行了比较,取得了较好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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