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Artificial neural networks in prediction of mechanical behavior of concrete at high temperature

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Title Artificial neural networks in prediction of mechanical behavior of concrete at high temperature
 
Creator MUKHERJEE, ABHIJIT
BISWAS, SUDIP NAG
 
Subject compressive strength
fission reactor materials
high temperature effects
stress-strain relations
 
Description The behavior of concrete structures that are exposed to extreme thermo-mechanical loading is an issue of great
importance in nuclear engineering. The mechanical behavior of concrete at high temperature is non-linear. The
properties that regulate its response are highly temperature dependent and extremely complex. In addition, the
constituent materials, e.g. aggregates, influence the response significantly. Attempts have been made to trace the
stress–strain curve through mathematical models and rheological models. However, it has been difficult to include all
the contributing factors in the mathematical model. This paper examines a new programming paradigm, artificial
neural networks, for the problem. Implementing a feedforward network and backpropagation algorithm the
stress–strain relationship of the material is captured. The neural networks for the prediction of uniaxial behavior of
concrete at high temperature has been presented here. The results of the present investigation are very encouraging.
 
Publisher Elsevier
 
Date 2009-04-28T05:24:06Z
2011-12-08T06:36:58Z
2011-12-26T13:01:42Z
2011-12-27T05:46:10Z
2009-04-28T05:24:06Z
2011-12-08T06:36:58Z
2011-12-26T13:01:42Z
2011-12-27T05:46:10Z
1997
 
Type Article
 
Identifier Nuclear Engineering and Design 178(1), 1-11
0029-5493
10.1016/S0029-5493(97)00152-0
http://hdl.handle.net/10054/1252
http://dspace.library.iitb.ac.in/xmlui/handle/10054/1252
 
Language en