Analysis of Structural Impact and Crashworthiness using Experimental, Analytical and Computational Techniques: An Overview and Recent Developments

Liu, Yucheng; Chu, Stefan J.; Viera, Raul J.

doi:10.4273/ijvss.3.3.01

Cited by 2 publications

(1 citation statement)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thin-walled S-rail structures are the central components of vehicle's progressive crushing zones and absorb the highest amount of the kinetic energy during a frontal or rear collision. Various investigations on S-rail structures have addressed the effect of triggering mechanisms through changes in the cross section [30,31]. Typically, the design objective is to find a feasible geometry capable of sustaining high specific energy absorption through the structure's progressive folding.…”

Section: Conceptual Designmentioning

confidence: 99%

Thin-Walled Compliant Mechanism Component Design Assisted by Machine Learning and Multiple Surrogates

Tovar

Nutwell

et al. 2015

SAE Technical Paper Series

View full text Add to dashboard Cite

This work introduces a new design algorithm to optimize progressively folding thin-walled structures and in order to improve automotive crashworthiness. The proposed design algorithm is composed of three stages: conceptual thickness distribution, design parameterization, and multi-objective design optimization. The conceptual thickness distribution stage generates an innovative design using a novel one-iteration compliant mechanism approach that triggers progressive folding even on irregular structures under oblique impact. The design parameterization stage optimally segments the conceptual design into a reduced number of clusters using a machine learning K-means algorithm. Finally, the multiobjective design optimization stage finds non-dominated designs of maximum specific energy absorption and minimum peak crushing force. The proposed optimization problem is addressed by a multiobjective genetic algorithm on sequentially updated surrogate models, which are optimally selected from a set of 24 surrogates. The effectiveness of the design algorithm is demonstrated on an S-rail thin-walled structure. The best compromised Pareto design increases specific energy absorption and decreases peak crushing force in the order of 8% and 12%, respectively. Recently, our research group has proposed the use of HCA topometry (thickness distribution) methods for compliant, plastically deformable structures to support the generation of conceptual design for progressively folding thin-walled components including S-rails [28]. This method follows the design principles of compliant mechanisms and their ability to transfer force and displacement from a given input

show abstract

Section: Conceptual Designmentioning

confidence: 99%