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A finite element–guided mathematical surrogate modeling approach for assessing occupant injury trends across variations in simplified vehicular impact conditions

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Abstract

A finite element (FE)–guided mathematical surrogate modeling methodology is presented for evaluating relative injury trends across varied vehicular impact conditions. The prevalence of crash-induced injuries necessitates the quantification of the human body’s response to impacts. FE modeling is often used for crash analyses but requires time and computational cost. However, surrogate modeling can predict injury trends between the FE data, requiring fewer FE simulations to evaluate the complete testing range. To determine the viability of this methodology for injury assessment, crash-induced occupant head injury criterion (HIC15) trends were predicted from Kriging models across varied impact velocities (10–45 mph; 16.1–72.4 km/h), locations (near side, far side, front, and rear), and angles (−45 to 45°) and compared to previously published data. These response trends were analyzed to locate high-risk target regions. Impact velocity and location were the most influential factors, with HIC15 increasing alongside the velocity and proximity to the driver. The impact angle was dependent on the location and was minimally influential, often producing greater HIC15 under oblique angles. These model-based head injury trends were consistent with previously published data, demonstrating great promise for the proposed methodology, which provides effective and efficient quantification of human response across a wide variety of car crash scenarios, simultaneously.

Graphical abstract

This study presents a finite element-guided mathematical surrogate modeling methodology to evaluate occupant injury response trends for a wide range of impact velocities (10–45 mph), locations, and angles (−45 to 45°). Head injury response trends were predicted and compared to previously published data to assess the efficacy of the methodology for assessing occupant response to variations in impact conditions. Velocity and location were the most influential factors on the head injury response, with the risk increasing alongside greater impact velocity and locational proximity to the driver. Additionally, the angle of impact variable was dependent on the location and, thus, had minimal independent influence on the head injury risk.

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Acknowledgements

The authors would like to acknowledge the support of the Center for Advanced Vehicular Systems (CAVS) at Mississippi State University. This material is based upon the work supported by ERDC under Contract No. W912HZ-17-C-0021. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the ERDC. Public release; distribution unlimited.

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Authors and Affiliations

  1. Center for Advanced Vehicular Systems, Mississippi State University, 200 Research Blvd, Starkville, MS, 39759, USA

    P. R. Berthelson, J. W. Wood, G. G. Stubblefield, M. F. Horstemeyer & R. K. Prabhu

  2. Department of Agricultural and Biological Engineering, Mississippi State University, Mississippi State, MS, 39762, USA

    P. R. Berthelson, J. W. Wood & R. K. Prabhu

  3. Department of Mechanical and Aerospace Engineering, University at Buffalo, 246 Bell Hall, Buffalo, NY, 14260, USA

    P. Ghassemi & S. Chowdhury

  4. Department of Mechanical Engineering, Mississippi State University, Mississippi State, MS, 39762, USA

    G. G. Stubblefield & M. F. Horstemeyer

  5. School of Engineering, Cardiff University, Cardiff, Wales, CF10 3AT, UK

    A. J. Al-Graitti & M. D. Jones

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Berthelson, P.R., Ghassemi, P., Wood, J.W. et al. A finite element–guided mathematical surrogate modeling approach for assessing occupant injury trends across variations in simplified vehicular impact conditions. Med Biol Eng Comput 59, 1065–1079 (2021). https://doi.org/10.1007/s11517-021-02349-3

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