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A modified finite element dummy model of Chinese adult male used for train collision simulations

Zhenhao Yu, Shaodong Zheng, Kai Liu, Zhipeng Gao, Longmao Zhao and Lin Jing

International Journal of Rail Transportation, 2024, vol. 12, issue 4, 709-732

Abstract: This work established a modified finite element (FE) dummy model representing the Chinese 50th percentile males through the whole segment scaling method, referring to the Total Human Model for Safety (THUMS-AM50) of European and American 50th percentile males. The head, neck, chest, abdomen, and knee-thigh-hip (KTH) of the modified model were validated, respectively, by the cadaver experimental results. Integrating the dummy models with a four-car marshalling train collision FE model, we analysed the dynamic response in terms of human body posture, head, and neck injuries of the Chinese 50th percentile males and the European and American 50th percentile males during the frontal train collision process. The corresponding simulation results fitted well with the experimental tests, indicating that the established modified model exerted great biological fidelity. Compared with European-American 50th percentile males, the Von-Mises stress, shear stress, maximum principal strain (MPS), and the cumulative strain damage measure CSDM0.15 of the brain in the Chinese 50th percentile males were approximately higher by 22.21%, 19.85%, 36.58%, and 47.55%, respectively. That meant the Chinese males might be at a higher risk of brain contusion and diffuse axonal injury (DAI) during the train collision. Meanwhile, the Chinese 50th percentile males had more severe neck extension, especially the maximum cervical vertebrae Von-Mises stress and neck injury predictor (Nij) were increased by 30.3% and 50%, respectively. The established modified model could provide a more accurate simulation for predicting the Chinese body injury response during the train collision.

Date: 2024
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DOI: 10.1080/23248378.2023.2201585

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International Journal of Rail Transportation is currently edited by Wanming Zhai and Kelvin C. P. Wang

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