吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (4): 963-967.doi: 10.13229/j.cnki.jdxbgxb201404010

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Neural network-based calculation of deflection increasing coefficient of steel-concrete composite beam

WEI Hai-bin, ZHANG Yang-peng, JIAO Yu-bo, LIU Han-bing   

  1. College of Traffic, Jilin University, Changchun 130022, China
  • Received:2013-01-05 Online:2014-07-01 Published:2014-07-01

Abstract: A neural network-based calculation method of deflection increasing coefficient of steel-concrete composite beam is proposed. This method takes the complexity and limitation of existing methods into consideration. The simply supported composite beam under concentrated load and uniformly distributed load is taken as example. Considering the effect of interface slip, the concept of deflection increasing coefficient is put forward. Sample data of the finite element model of composite beam are generated from simulation on ANSYS. BP neural network is trained and texted first using the sample data; then, it is applied to obtain the analytical formula of the deflection increasing coefficient.

Key words: road engineering, composite beam, deflection increasing coefficient, neural network, slip effect

CLC Number: 

  • U448
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