Crashworthiness Optimization of Nested and Concentric Circular Tubes Using Response Surface Methodology and Genetic Algorithm
Crashworthiness Optimization of Nested and Concentric Circular Tubes Using Response Surface Methodology and Genetic Algorithm
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DOI：
10.1590/1679-78254385
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发表时间：
2018-02
影响因子：
1.2
通讯作者：
Fatih Usta;Zana Eren;H. Kurtaran;H. Türkmen;Zafer Kazancı;Z. Mecitoğlu
中科院分区：
文献类型：
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作者：
Fatih Usta;Zana Eren;H. Kurtaran;H. Türkmen;Zafer Kazancı;Z. Mecitoğlu
本文采用有限元模型、响应面模型和遗传算法对嵌套同心圆管在冲击载荷作用下的耐撞性进行了优化。由于比能量吸收（SEA）和碰撞力效率（CFE）是评估耐撞性能的重要指标，因此在耐撞性能优化中采用了这些指标。采用三根同心管的长度和厚度以及一根同心管的半径作为设计变量，它们是SEA和CFE的有效参数。为了减少优化过程的计算成本，在进一步的计算中，建立了简单且计算成本低廉的响应面模型来取代有限元分析。应用非支配排序遗传算法NSGAII求解Pareto最优解。给出了不同选择设计的优化结果，表明了多目标函数的相对重要性。结果表明，与质量相同的单管相比，采用嵌套管可以减轻车辆的总重量。这些设计可以在实际中采用。
In this study crashworthiness optimization of nested and concentric circular tubes under impact loading is performed by coupling Finite Element model, Response Surface Models and Genetic Algorithm. Specific Energy Absorption SEA and Crash Force Efficiency CFE are used in crashworthiness optimization since these criteria are important indicators for evaluating crashworthiness performance. Length and thickness of three concentric tubes as well as radius of one tube are adopted as design variables which are effective parameters on SEA and CFE. To reduce the computational cost of the optimization procedure, simple and computationally cheap Response Surface Models are created to replace finite element analyses in further calculations. The Non‐dominated Sorting Genetic Algorithm –II NSGAII is applied to obtain the Pareto optimal solutions. Optimization results are presented for different selected designs that indicate relative importance of multi‐objective functions. Results show that the total weight of the vehicles can be reduced by using nested tubes comparing to single tubes with identical masses. These designs can be adopted for use in practice.