Techno Press

Structural Engineering and Mechanics   Volume 39, Number 2, July25 2011, pages 267-285
Prediction of moments in composite frames considering cracking and time effects using neural network models
Umesh Pendharkar, Sandeep Chaudharyb and A.K. Nagpal

Abstract     [Full Text]
    There can be a significant amount of moment redistribution in composite frames consisting of steel columns and composite beams, due to cracking, creep and shrinkage of concrete. Considerable amount of computational effort is required for taking into account these effects for large composite frames. A methodology has been presented in this paper for taking into account these effects. In the methodology that has been demonstrated for moderately high frames, neural network models are developed for rapid prediction of the inelastic moments (typically for 20 years, considering instantaneous cracking, and time effects, i.e., creep and shrinkage, in concrete) at a joint in a frame from the elastic moments (neglecting instantaneous cracking and time effects). The proposed models predict the inelastic moment ratios (ratio of elastic moment to inelastic moment) using eleven input parameters for interior joints and seven input parameters for exterior joints. The training and testing data sets are generated using a hybrid procedure developed by the authors. The neural network models have been validated for frames of different number of spans and storeys. The models drastically reduce the computational effort and predict the inelastic moments, with reasonable accuracy for practical purposes, from the elastic moments, that can be obtained from any of the readily available software.
Key Words
    composite frames; cracking; creep; shrinkage; neural networks
Umesh Pendharkar: Civil Engineering, Ujjain Engineering College, Ujjain, India
Sandeep Chaudharyb: Structural Engineering, Malaviya National Institute of Technology, Jaipur, India
A.K. Nagpal: Civil Engineering, Indian Institute of Technology Delhi, New Delhi, India

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