Artificial neural networks in prediction of mechanical behavior of concrete at high temperature
DSpace at IIT Bombay
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Title |
Artificial neural networks in prediction of mechanical behavior of concrete at high temperature
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Creator |
MUKHERJEE, ABHIJIT
BISWAS, SUDIP NAG |
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Subject |
compressive strength
fission reactor materials high temperature effects stress-strain relations |
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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. |
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Publisher |
Elsevier
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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 |
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Type |
Article
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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 |
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Language |
en
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