An adaptive marine predator algorithm based optimization method for hood lightweight design

IF 4.8 2区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Computational Design and Engineering Pub Date : 2023-04-29 DOI:10.1093/jcde/qwad047
Chenglin Zhang, Zhicheng He, Qiqi Li, Yong Chen, Shaowei Chen, X. Nie
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Abstract

The lightweight design of the hood is crucial for the structural optimization of an entire vehicle. However, traditional high-fidelity-based lightweight methods are time-consuming due to the complex structures of the hood, and the lightweight results heavily rely on engineering experiences. To this end, an improved adaptive marine predator algorithm (AMPA) is proposed to solve this problem. Compared to the original marine predator algorithm (MPA), the proposed AMPA adapts to optimization problems through three enhancements, including chaotic theory-based initialization, a mixed search strategy, and dynamic partitioning of iteration phases. Experimental comparisons of AMPA, MPA, and eight state-of-the-art algorithms are conducted on IEEE CEC2017 benchmark functions. AMPA outperforms the others in both 30- and 50-dimensional experiments. Friedman and Wilcoxon’s sign-rank tests further confirm AMPA’s superiority and statistical significance. An implicit parametric model of the hood is generated, and the critical design variables are determined through global sensitivity analysis to realize hood lightweight. The stacking method is employed to construct a surrogate meta-model of the hood to accelerate the optimization efficiency of the vehicle hood. Utilizing the meta-model and the proposed AMPA, the hood mass is reduced by 7.43% while all six static and dynamic stiffness metrics are enhanced. The effectiveness of the proposed optimization method is validated through finite element analysis.
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基于自适应海洋捕食者算法的发动机罩轻量化优化设计方法
引擎盖的轻量化设计对于整车的结构优化至关重要。然而,传统的基于高保真度的轻量化方法由于发动机罩结构复杂,耗时长,而且轻量化结果严重依赖工程经验。为此,提出了一种改进的自适应海洋捕食者算法(AMPA)来解决这一问题。与原有的海洋捕食者算法(MPA)相比,本文提出的海洋捕食者算法通过混沌初始化、混合搜索策略和迭代阶段动态划分三方面的改进来适应优化问题。在IEEE CEC2017基准函数上对AMPA、MPA和八种最先进的算法进行了实验比较。AMPA在30维和50维的实验中都优于其他方法。Friedman和Wilcoxon的sign-rank检验进一步证实了AMPA的优越性和统计学显著性。建立了发动机罩的隐式参数化模型,通过全局灵敏度分析确定了关键设计变量,实现了发动机罩的轻量化。采用叠加法构建了引擎盖的代理元模型,提高了引擎盖的优化效率。利用元模型和提出的AMPA,发动机罩质量降低了7.43%,同时所有六个静态和动态刚度指标都得到了增强。通过有限元分析验证了所提优化方法的有效性。
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来源期刊
Journal of Computational Design and Engineering
Journal of Computational Design and Engineering Computer Science-Human-Computer Interaction
CiteScore
7.70
自引率
20.40%
发文量
125
期刊介绍: Journal of Computational Design and Engineering is an international journal that aims to provide academia and industry with a venue for rapid publication of research papers reporting innovative computational methods and applications to achieve a major breakthrough, practical improvements, and bold new research directions within a wide range of design and engineering: • Theory and its progress in computational advancement for design and engineering • Development of computational framework to support large scale design and engineering • Interaction issues among human, designed artifacts, and systems • Knowledge-intensive technologies for intelligent and sustainable systems • Emerging technology and convergence of technology fields presented with convincing design examples • Educational issues for academia, practitioners, and future generation • Proposal on new research directions as well as survey and retrospectives on mature field.
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