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Prediction of buckling load of columns using artificial neural networks

DSpace at IIT Bombay

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Title Prediction of buckling load of columns using artificial neural networks
 
Creator MUKHERJEE, A
DESHPANDE, JM
ANMALA, J
 
Description A number of investigators have proposed semiempirical formulas for the critical buckling load of slender columns. The departure from the assumptions of the elastic-plastic theory makes the task of incorporating all the features of real-life columns into a single formula very difficult. As a result, semiempirical formulas, adopted for design specifications often follow a lower bound to experimental observations to include a variety of column types. Therefore, a significant portion of the actual column strength remains unutilized, when such a lower bound is adopted in the design of axially compressed members. This technical note reports development of a tool for the prediction of buckling load of columns, which requires minimum assumptions using neural computing techniques. This concept can be extended to include a variety of column types in a single model for the buckling load of columns. This concept can also be further extended for reliability analysis as the network can also predict the standard deviation in the column strength.
 
Publisher ASCE-AMER SOC CIVIL ENG
 
Date 2011-07-18T10:36:25Z
2011-12-26T12:50:33Z
2011-12-27T05:35:58Z
2011-07-18T10:36:25Z
2011-12-26T12:50:33Z
2011-12-27T05:35:58Z
1996
 
Type Article
 
Identifier JOURNAL OF STRUCTURAL ENGINEERING-ASCE, 122(11), 1385-1387
0733-9445
http://dx.doi.org/10.1061/(ASCE)0733-9445(1996)122:11(1385)
http://dspace.library.iitb.ac.in/xmlui/handle/10054/4882
http://hdl.handle.net/10054/4882
 
Language en