Beam Element Model Optimization Applying Artificial Neural Networks on BIW Concept Design

Format:

Conference/Event

Author/Creator:

Dai, Yi, author.

Conference Name:

Asia Pacific Automotive Engineering Conference (2007-08-05 : Hollywood, California, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2007

Summary:

Vehicle body-in-white crash models are important for crashworthiness analysis. Conventional finite element methods usually deal with a large sized computational model and thus hinder efficient design evaluation. The proposed beam element method, with a significant reduction of model size and computation time, is capable of extracting essential safety dynamic characteristics. An artificial neural network is employed and the recurrent back-propagation learning rule trains the network to obtain optimized beam element features. Our analysis shows that the optimized beam element model can accurately capture the frontal crash characteristics of the impacting structures, and predict the vehicle body-in-white crash performance in conceptual design stage

Notes:

Vendor supplied data

Publisher Number:

2007-01-3712

Access Restriction:

Restricted for use by site license