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2009 Second International Symposium on Computational Intelligence and Design
Comparison of Artificial Neural Networks with Response Surface Models in Characterizing the Impact Damage Resistance of Sandwich Airframe Structures
Changsha, Hunan, China
December 12-December 14
ISBN: 978-0-7695-3865-5
ASCII Text
x 
 
Jian Li, Xiuhua Chen, Hai Wang, "Comparison of Artificial Neural Networks with Response Surface Models in Characterizing the Impact Damage Resistance of Sandwich Airframe Structures," Computational Intelligence and Design, International Symposium on, vol. 2, pp. 210-215, 2009 Second International Symposium on Computational Intelligence and Design, 2009.
 
 
BibTex
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@article{ 10.1109/ISCID.2009.200,
author = {Jian Li and Xiuhua Chen and Hai Wang},
title = {Comparison of Artificial Neural Networks with Response Surface Models in Characterizing the Impact Damage Resistance of Sandwich Airframe Structures},
journal ={Computational Intelligence and Design, International Symposium on},
volume = {2},
year = {2009},
isbn = {978-0-7695-3865-5},
pages = {210-215},
doi = {http://doi.ieeecomputersociety.org/10.1109/ISCID.2009.200},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Computational Intelligence and Design, International Symposium on
TI - Comparison of Artificial Neural Networks with Response Surface Models in Characterizing the Impact Damage Resistance of Sandwich Airframe Structures
SN - 978-0-7695-3865-5
SP210
EP215
A1 - Jian Li,
A1 - Xiuhua Chen,
A1 - Hai Wang,
PY - 2009
VL - 2
JA - Computational Intelligence and Design, International Symposium on
ER -
 
In the development of a damage tolerance plan for composite airframe structures, the way to characterize the impact damage of sandwich composites under different levels of impact events and material property is crucial. The aim of the present research is to investigate the influence of material configuration and impact parameters on damage resistance responses of composite sandwich structures comprised of carbon-epoxy woven fabric facesheets and Nomex honeycomb cores. Two methods, artificial neural network and classic response surface methodology were used to predict the relationship between the impact damage response and its dependent parameters. The results obtained through artificial neural networks were compared with those through response surface methodology.
Citation:
Jian Li, Xiuhua Chen, Hai Wang, "Comparison of Artificial Neural Networks with Response Surface Models in Characterizing the Impact Damage Resistance of Sandwich Airframe Structures," iscid, vol. 2, pp.210-215, 2009 Second International Symposium on Computational Intelligence and Design, 2009
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