耐撞性
拉丁超立方体抽样
仿生学
遗传算法
撞车
结构工程
工程类
计算机科学
有限元法
数学优化
蒙特卡罗方法
数学
人工智能
统计
程序设计语言
作者
Chunyan Wang,Yan Li,Wanzhong Zhao,Songchun Zou,Zailin Guan,YuanLong Wang
标识
DOI:10.1016/j.ijmecsci.2018.01.032
摘要
In order to improve the crashworthiness and energy absorption performance, this paper introduces the structural bionics to the structural design of crash box and proposes a novel structure. Taking the human tibia as a bionic object, the novel crash box is composed of a concave structure shell and an inner core filled with negative Poisson's ratio (NPR) structure material. In view of the gradient characteristics of the cancellous bone structure of the tibia, the NPR inner core is designed as a functional gradient distribution structure along the longitudinal direction of the crash box. Based on this, by combining the optimal Latin hypercube design and response surface methodology, a multi-objective optimization design is conducted for the novel crash box based on archive-based micro genetic algorithm (AMGA) and improved non-dominated sorting genetic algorithm (NSGA-II). Simulation results show that the novel crash box optimized by NSGA-II algorithm can improve the energy absorption characteristics and comprehensive crashworthiness more effectively, and make the collision process controllable and stable. The results of this paper can provide some reference for the design and optimization of the crash box.
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