Inverse Analysis of Material Parameters of Multiple Foam Layers Based on Artificial Neural Network

Abstract:

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Closed cell polymeric foams are widely used in sport and medical equipments. In this study, an artificial neural network (ANN) based inverse finite element (FE) program has been developed and used to predict the nonlinear material properties of EVA foams with multiple layers. A 2-D parametric FE model was developed and validated against experimental data. Systematic data from FE simulations was used to train and validate the ANN model. The accuracy and validity of the ANN method were assessed based on both blind tests and experimental data. Results showed that the proposed artificial neural network model is robust and efficient in predicating the nonlinear parameters of foam materials.

Info:

Periodical:

Advanced Materials Research (Volumes 189-193)

Edited by:

Zhengyi Jiang, Shanqing Li, Jianmin Zeng, Xiaoping Liao and Daoguo Yang

Pages:

3313-3316

DOI:

10.4028/www.scientific.net/AMR.189-193.3313

Citation:

X. X. Su et al., "Inverse Analysis of Material Parameters of Multiple Foam Layers Based on Artificial Neural Network", Advanced Materials Research, Vols. 189-193, pp. 3313-3316, 2011

Online since:

February 2011

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Price:

$35.00

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