Multiple-Criteria Evaluation of Thin-Walled Energy-Absorbing Structures of Train Under Fuzzy Environment: Modeling and Algorithm

• Published in: IEEE access Vol. 9; pp. 150393 - 150402
• Main Authors: Li, Hongliang, Qiu, Jiangjie, Li, Tao, Xie, Guoquan, Wang, Danqi, Wang, Wenjie
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Absorption; Algorithms; Aluminum alloys; Biological properties; Biological system modeling; Biomimetics; Bionics; Computer crashes; Configuration management; Crashworthiness; Decision support systems; Design engineering; Empirical analysis; Energy absorbing structures; Energy absorption; Environment models; evaluation algorithm; Finite element analysis; Finite element method; Fuzzy logic; Fuzzy sets; High speed rail; high-speed train; Impact strength; Light levels; Mathematical models; Mechanical properties; Multiple criterion; Reliability analysis; Sensitivity analysis; Strain; sustainability; Sustainable development; Thin wall structures; transportation; Transportation systems
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2021.3125397

High-speed train is of great significance in the modern comprehensive transportation system. Bio-inspired engineering design, with the excellent structural and mechanical properties of the biological systems, has been a widespread concern in the design of thin-walled energy-absorbing structures for high-speed trains. However, different structural characteristics have significant effects on the performance of crashworthiness and lightweight level. Collaboration matching of performance between design and operational processes considering the engineering requirements has become an urgent problem. This study constructs the finite element model of the horsetail-bionic thin-walled energy-absorbing structure, which is inspired by horsetail's structural characteristics. An existing high-speed train is set as the empirical case. The effects of the number of cross-section configurations on the performances of crashworthiness and light level are explored under the condition of train collision. A hybrid decision-making methodology that combines fuzzy DEMATEL and TODIM is proposed. The result shows the horsetail-bionic thin-walled structure with six-floor plates is the optimal alternative considering the multiple criteria. In addition, comparison with the existing methods and sensitivity analysis are conducted to validate the reliability of this proposed approach. This study provides an effective decision support tool for crashworthiness evaluation or structural feature selection of thin-walled structures.