Search Results

This paper represents the development of a new design methodology based on data mining theory for decision making in vehicle crashworthy components (or parts) development. The new methodology allows exploring the big crash simulation dataset to discover the underlying complicated relationships between vehicle crash responses and design variables at multi-levels, and deriving design rules based on the whole vehicle safety requirements to make decisions towards the component and sub-component level design. The method to be developed will resolve the issue of existing design approaches for vehicle crashworthiness, i.e. limited information exploring capability from big datasets, which may hamper the decision making and lead to a nonoptimal design. A preliminary design case study is presented to demonstrate the performance of the new method. This method will have direct impacts on improving vehicle safety design and can readily be applied to other complex systems.

Numerical models of Hybrid III had been widely used to study the effect of underbody blast loading on lower extremities. These models had been primarily validated for automotive loading conditions of shorter magnitude in longer time span which are different than typical blast loading conditions of higher magnitude of shorter duration. Therefore, additional strain rate dependent material models were used to validate lower extremity of LSTC Hybrid III model for such loading conditions. Current study focuses on analyzing the mitigating effect of combat boots in injury responses with the help of validated LSTC Hybrid III model. Numerical simulations were run for various impactor speeds using validated LSTC Hybrid III model without any boot (bare foot) and with combat boot.