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Computers and Concrete
  Volume 18, Number 6, December 2016, pages 1113-1134

Rapid prediction of inelastic bending moments in RC beams considering cracking
K.A.Patel, SandeepChaudhary and A.K.Nagpal

    A methodology using neural networks has been proposed for rapid prediction of inelastic bending moments in reinforced concrete continuous beams subjected to service load. The closed form expressions obtained from the trained neural networks take into account cracking in concrete at in-span and at near the internal supports and tension stiffening effect. The expressions predict the inelastic moments (considering the concrete cracking) from the elastic moments (neglecting the concrete cracking) at supports. Three separate neural networks are trained since these have been postulated to represent all the beams having any number of spans. The training, validating, and testing data sets for the neural networks are generated using an analytical-numerical procedure of analysis. The proposed expressions are verified for example beams of different number of spans and cross-section properties and the errors are found to be small. The proposed expressions, at minimal input data and computation effort, yield results that are close to FEM results. The expressions can be used in preliminary every day design as they enable a rapid prediction of inelastic moments and require a computational effort that is a fraction of that required for the available methods in literature.
Key Words
    bending moment; closed form expression; cracking; neural network; reinforced concrete; service load
K.A.Patel and A.K.Nagpal: Civil Engineering Department,Indian Institute of Technology Delhi,NewDelhi 110016,India

Sandeep Chaudhary: Civil Engineering Department, Malaviya National Institute of Technology Jaipur, Jaipur 302017, India

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