Optimization of Occupant Restraint System Using Machine Learning for THOR-M50 and Euro NCAP

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS

ACS Applied Bio Materials Pub Date : 2024-01-18 DOI:10.3390/machines12010074

Jaehyuk Heo, Min Gi Cho, Taewung Kim

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引用次数: 0

Abstract

In this study, we propose an optimization method for occupant protection systems using a machine learning technique. First, a crash simulation model was developed for a Euro NCAP MPDB frontal crash test condition. Second, a series of parametric simulations were performed using a THOR dummy model with varying occupant safety system design parameters, such as belt attachment locations, belt load limits, crash pulse, and so on. Third, metamodels were developed using neural networks to predict injury criteria for a given occupant safety system design. Fourth, the occupant safety system was optimized using metamodels, and the optimal design was verified using a subsequent crash simulation. Lastly, the effects of design variables on injury criteria were investigated using the Shapely method. The Euro NCAP score of the THOR dummy model was improved from 14.3 to 16 points. The main improvement resulted from a reduced risk of injury to the chest and leg regions. Higher D-ring and rearward anchor placements benefited the chest and leg regions, respectively, while a rear-loaded crash pulse was beneficial for both areas. The sensitivity analysis through the Shapley method quantitatively estimated the contribution of each design variable regarding improvements in injury metric values for the THOR dummy.

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利用机器学习优化 THOR-M50 和欧洲 NCAP 的乘员约束系统

在本研究中，我们提出了一种利用机器学习技术优化乘员保护系统的方法。首先，针对欧洲 NCAP MPDB 正面碰撞测试条件开发了碰撞模拟模型。其次，使用 THOR 假人模型进行了一系列参数模拟，并改变了乘员安全系统的设计参数，如安全带连接位置、安全带负载限制、碰撞脉冲等。第三，利用神经网络开发了元模型，以预测特定乘员安全系统设计的伤害标准。第四，利用元模型对乘员安全系统进行优化，并在随后的碰撞模拟中对优化设计进行验证。最后，使用 Shapely 方法研究了设计变量对伤害标准的影响。THOR 假人模型的欧洲 NCAP 分数从 14.3 分提高到 16 分。主要的改进来自于胸部和腿部受伤风险的降低。较高的 D 形环和向后的锚定位置分别有利于胸部和腿部区域，而后部加载的碰撞脉冲则有利于这两个区域。通过 Shapley 方法进行的敏感性分析定量估算了每个设计变量对改善 THOR 假人伤害度量值的贡献。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

ACS Applied Bio Materials Chemistry-Chemistry (all)

CiteScore

9.40

自引率

2.10%

发文量

464

期刊介绍： ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.