Paper Title:
Inverse Analysis of Material Parameters of Multiple Foam Layers Based on Artificial Neural Network
  Abstract

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, Y. D. Gu, J.P. Finlay, I.D. Jenkinson, X. J. Ren, "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
$32.00
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