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An Application of Cluster Analysis to Dummy Injury Readings in a Frontal Crash

机译:集群分析在正面崩溃中对伪损伤读数的应用

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Public concern about the crashworthiness of vehicles has been continuously rising in recent years. Crashworthiness is evaluated under various crash configurations, including frontal collisions, in regulatory testing and in New Car Assessment Programs. Accordingly, vehicle manufacturers must deploy sophisticated product development strategies and redouble their engineering efforts in order to develop vehicles that satisfy the specified requirements for crashworthiness. Computer simulation is one effective approach to resolving this issue in that it provides a valuable tool for conducting multiple parameter studies and iterations in a short period of time. However, it is no easy task for CAE engineers to analyze the large volumes of calculation results obtained in frontal crash simulations and to understand the phenomena involved. One reason is that a great deal of time is needed to understand the many calculation results comprehensively, despite the fact that frontal crash phenomena are interrelated in complex ways. This paper presents an example of a parameter study in which cluster analysis was used effectively to examine front-seat passenger restraint systems in a frontal crash. In a cluster analysis, calculation results are grouped into clusters having the same response characteristics. Because the design variables are also similarly clustered, engineers can gain a deeper understanding of the phenomena of interest. Two types of simulation models were used in this study. First, a multibody system (MBS) model was used as a simple mass-spring model to conduct a parameter study. This simple model made it possible to perform many calculations in a broad design space in a short period of time. Cluster analysis was then applied to analyze the calculation results of the parameter study. Using this method to understand simulation results enables engineers to formulate hypotheses about design guidelines for satisfying safety performance requirements. As the next step, a detailed finite element model that facilitated highly accurate simulations was used to verify the validity of the hypotheses. This study made clear the influence of pelvis behavior on dummy chest injury readings, and the results also demonstrated the utility of cluster analysis in trying to understand the complex phenomena involved in a frontal crash.
机译:近年来,对车辆克鲁特的公众关注持续上升。在各种崩溃配置中评估了崩溃性,包括额外碰撞,监管检测和新的汽车评估计划。因此,车辆制造商必须部署复杂的产品开发策略,并加倍工程努力,以开发满足特定持续性要求要求的车辆。计算机仿真是解决此问题的一种有效方法,因为它提供了在短时间内进行多个参数研究和迭代的有价值的工具。然而,CAE工程师不易任务,以分析在正面碰撞模拟中获得的大量计算结果,并了解所涉及的现象。一个原因是,尽管正面碰撞现象以复杂的方式相互关联,但是全面了解许多计算结果需要大量的时间。本文介绍了一个参数研究的示例,其中使用集群分析来有效地检查正面碰撞中的前座椅乘客约束系统。在集群分析中,计算结果被分组成具有相同响应特性的簇。由于设计变量也类似地聚集,因此工程师可以更深入地了解感兴趣的现象。本研究使用了两种类型的仿真模型。首先,将多体系系统(MBS)模型用作简单的质量弹簧模型来进行参数研究。这种简单的模型使得可以在短时间内在广泛的设计空间中执行许多计算。然后应用聚类分析来分析参数研究的计算结果。使用这种方法来了解模拟结果,使工程师能够制定关于用于满足安全性能要求的设计指南的假设。作为下一步,使用便于高精度模拟的详细有限元模型来验证假设的有效性。本研究明确了骨盆行为对假胸部损伤读数的影响,结果还证明了集群分析试图了解额外碰撞中涉及的复杂现象的效用。

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