粒子群优化
本构方程
算法
群体行为
多群优化
计算机科学
粒子(生态学)
数学优化
材料科学
数学
工程类
结构工程
人工智能
有限元法
地质学
海洋学
作者
Xiaoxiao Wei,Fan Tan,Peipei Yang,Hongchen Pan
标识
DOI:10.1088/2053-1591/ad8396
摘要
Abstract Utilizing the Gleeble-3500 thermal simulation apparatus, a thermal compression assay was performed on 41CrS4 steel within the temperature range of 900 °C to 1200 °C, featuring a strain rate of 0.01 to 5 s −1 , to derive its flow stress curve. The evaluation of the Arrhenius equation parameters was adeptly carried out by deploying a sophisticated particle swarm optimization algorithm. Through rigorous analysis, the correlation coefficient and the mean absolute deviation were calculated to quantify the alignment between the predictive accuracy of the developed model and the empirical data. The findings demonstrate the ability of the particle swarm optimization algorithm to significantly enhance the precision of the constitutive model. This augmented level of accuracy substantively increases the model’s utility and reliability for simulations of high-temperature material forming processes.
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