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论文类型：期刊论文

发表时间：2016-09-01

发表刊物：INTERNATIONAL JOURNAL OF IMPACT ENGINEERING

收录刊物：SCIE、EI、Scopus

卷号：95

页面范围：72-88

ISSN号：0734-743X

关键字：Thin-walled structure; Functionally graded strength (FGS); High strength boron steel; Crashworthiness; Multi-objective optimization

摘要：Thin-walled structures have been widely used as energy absorbers in industries such as automobile, shipping and aerospace. Different from recent well-studied columns consisting of aluminum, this paper introduced a kind of quenched boron steel column formed by hot stamping technology, with wall strength varying along the axial direction with a specific gradient, i.e. functionally graded strength (FGS). These FGS structures are found to have higher crashworthiness in terms of peak crash force (PCF) and specific energy absorption (SEA) compared with the counterpart structures with uniform strength (US). Based on a series of numerical simulation results, it revealed that the crashing behavior of FGS columns is significantly affected by both the strength gradient and the strength in the impact end. To optimize the crashworthiness (PCF and SEA) of the FGS structures, multi-optimization based on different metamodeling techniques such as response surface method (RSM), radial basis function (RBF) neural network model, kriging (KRG) model and optimization algorithm of non-dominated sorting genetic algorithm (NSGA-II) are performed. Pareto fronts of several alternative thicknesses were obtained to provide guidance for the FGS column design and give a good insight into actual crashing engineering. It is interesting to find that the gradient exponent is taken as the main design variable when the PCF is restricted below a certain value while the parameter of steel strength in impact end will be taken as the main design variable on the contrary. The comparison of Pareto fronts between the FGS and US columns showed that the FGS columns enhance the SEA and lower the PCF concurrently. Furthermore, among the three metamodeling techniques, the RSM models are proven to be the most suitable approach for the crashworthiness optimization of FGS structure. (C) 2016 Elsevier Ltd. All rights reserved.