Suppr超能文献

汽车-行人碰撞中下肢损伤的预测——真实事故研究。

Prediction of lower extremity injuries in car-pedestrian crashes - real-world accident study.

机构信息

Department of Mechanical Engineering, Indian Institute of Technology Delhi, New Delhi, India.

出版信息

Traffic Inj Prev. 2021;22(2):173-176. doi: 10.1080/15389588.2020.1866177. Epub 2021 Feb 2.

Abstract

OBJECTIVE

This study focusses on injury prediction capabilities of the THUMS (Total HUman Body Model for Safety) finite element human body model (FE-HBM) in real world car-pedestrian crashes.

METHODS

Ten cases of car-pedestrian crashes with incidence of lower extremity injuries were reconstructed using sequence of multi-body tools and finite element tools. Multi-body simulations were used to obtain relevant impact conditions like vehicle speed, pedestrian location etc. which were later used as initial conditions in finite element simulations. Estimated injury from the FE simulation were compared with the clinical records of victim.

RESULTS

The severity and location of injuries were correctly predicted in 8 out of 10 crashes that were considered. However, in remaining two cases injuries were under-predicted, and strain didn't reach the failure threshold level.

CONCLUSION

This study demonstrates that THUMS HBM well predicts pedestrian injuries in real-world crashes. However, a similar study with comprehensive crash site data and medical records of victims will enhance the confidence in results.

摘要

目的

本研究专注于 THUMS(用于安全的全人体模型)有限元人体模型(FE-HBM)在真实世界汽车-行人碰撞中对损伤的预测能力。

方法

使用多体工具和有限元工具序列,对 10 例下肢受伤的汽车-行人碰撞事故进行了重建。多体模拟用于获得相关的碰撞条件,如车辆速度、行人位置等,这些条件后来被用作有限元模拟的初始条件。将有限元模拟估计的损伤与受害者的临床记录进行比较。

结果

在考虑的 10 起事故中,有 8 起正确预测了损伤的严重程度和位置。然而,在其余的 2 起事故中,损伤被低估了,应变没有达到失效阈值水平。

结论

本研究表明,THUMS HBM 可以很好地预测真实世界碰撞中的行人损伤。然而,进行类似的研究,结合全面的碰撞现场数据和受害者的医疗记录,将增强对结果的信心。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验