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A Computationally Efficient Finite Element Pedestrian Model for Head Safety: Development and Validation.

Guibing Li1, Zheng Tan1, Xiaojiang Lv2,3

  • 1School of Mechanical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China.

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Summary
This summary is machine-generated.

A new, computationally efficient finite element (FE) pedestrian model was developed and validated. This tool aids in studying pedestrian head injuries from vehicle crashes, improving road safety research.

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Area of Science:

  • Biomechanics
  • Computational modeling
  • Road safety engineering

Background:

  • Head injuries in vehicle crashes pose significant risks to pedestrians.
  • Finite element (FE) simulations are crucial for understanding pedestrian head injury mechanisms.
  • Current FE human body models are computationally expensive, limiting broad impact scenario studies.

Purpose of the Study:

  • To develop and validate a computationally efficient FE pedestrian model.
  • To facilitate future research on pedestrian head safety.
  • To overcome limitations of existing models in terms of computing time.

Main Methods:

  • Development of a FE pedestrian model with 432,694 elements.
  • Validation of the model at segment and full body levels using cadaver test data.
  • Analysis of pedestrian responses under lateral impact loading and vehicle-to-pedestrian impact configurations.

Main Results:

  • The FE pedestrian model demonstrated responses within cadaver test corridors for knee, pelvis, thorax, and shoulder under lateral impact.
  • Upper body (head, T1, T8) trajectories showed good agreement with cadaver data in vehicle-to-pedestrian impacts.
  • The model's computational efficiency was established for broader application.

Conclusions:

  • The developed FE pedestrian model is a validated and computationally efficient tool.
  • This model can significantly contribute to pedestrian head safety studies.
  • It offers a valuable resource for simulating various impact scenarios in vehicle-pedestrian crashes.