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Accurate prediction of the responses from the anthropomorphic test devices (ATDs) in vehicle crash tests is critical to achieving better vehicle occupant performances. In recent years, automakers have used finite element (FE) models of the ATDs in computer simulations to obtain early assessments of occupant safety, and to aid in the development of occupant restraint systems. However, vehicle crash test results have variation, sometimes significant. This presents a challenge to assessing the accuracy of the ATD FE models, let alone improving them. To resolve this issue, it is important to understand the test variation and carefully select the target data for model improvement. This paper presents the work carried out by General Motors and Humanetics Innovative Solutions (formerly FTSS) in a joint project, aimed at improving the FE model of the Hybrid III-50 ATD (HIII-50) v5.1.

Process automation is one of the emerging technologies in the field of computer aided engineering (CAE). A majority of the CAE processes involve repetitive steps during the product development and enhancement phases. An effort is being made to improve the engineer's efficiency by automating the repetitive tasks. The objective of the current study is to demonstrate the capabilities of CAE or FE process automation. Using a CAE process authoring and execution environment, a process was developed for the standard neck pendulum certification for the FE Hybrid III 5th percentile female ATD model. Standard pre-processing tasks for the typical neck pendulum certification simulation such as ATD head/neck replacement and positioning, resolving connections, quality checks, boundary and loading conditions, contact definitions, etc. were defined as process steps. Solver execution and post-processing were also made part of the process automation for the review of results and report generation.