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Beam Element Model Optimization Applying Artificial Neural Networks on BIW Concept Design
Technical Paper
2007-01-3712
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
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.
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Citation
Dai, Y. and Duan, C., "Beam Element Model Optimization Applying Artificial Neural Networks on BIW Concept Design," SAE Technical Paper 2007-01-3712, 2007, https://doi.org/10.4271/2007-01-3712.Also In
References
- Omar, T. Eskandarian, A. Bedewi, N. Vehicle Crash Modelling Using Recurrent Neural Networks Mathematical and Computer Modelling 28 9 31 42 1998
- Kamal, M. M. Analysis and Simulation of Vehicle to Barrier Impact SAE Paper 700414 1970
- Mahmood, H. Paluezny, A. Analytical Technique for Simulating Crash Response of Vehicle Structures Composed of Beam Elements SAE Paper 860820 1986
- Ariyoshi, T. Development of a Beam Element Model for an Analysis of a Motor Vehicle Rear End Crash SAE Paper 900463 1990
- Takada, K. Abramowicz, W. Object-Oriented Formulation of the 3 rd Large Deformation Beam Element for Crash Applications SAE Paper 2003-01-2740 2003
- Hahm, S. Won, Y. Kim, D. Frontal Crash Feasibility Study using MADYMO 3D Frame Model SAE Paper 1999-01-0072 1999
- Deshpande, B.R. Gunasekar, T.J. Gupta, V. Jayaraman, S. Summers, S.M. Development of MADYMO Models of Passenger Vehicles for Simulating Side Impact Crashes SAE Paper 1999-01-2885 1999
- Chen, S.Y. An Approach for Impact Structure Optimization using the Robust Genetic Algorithm Finite Elements in Analysis and Design 37 431 446 2001
- Kurtaran, H. Eskandarian, A. Marzougui, D. Bedewi, N.E. Crashworthiness Design Optimization using Successive Response Surface Approximations Computational Mechanics 29 409 421 2002
- Amago, T. Sizing Optimization using Response Surface Method in FOA R&D Review of Toyota CRDL 37 1 1 7 2004
- Lanzi, L. Bisagni, C. Ricci, S. Neural Network Systems to Reproduce Crash Behavior of Structual Components Computers and Structures 82 93 108 2004
- Kirkpatrick, S.W. Simons, J.W. Antoum, T.H. Development and Validation of High Fidelity Vehicle Crash Simulation Models Proceedings of International Crashworthiness Conference 602 611 1998
- Bartlett, P.L. Anthony, M.N. Neural Network Learning: Theoretical Foundations Cambridge University Press London 1999
- Ewins, D.J. Modal Testing - Theory, Practice and Application Research Studies Press England 2000