Abstract
In this study, a model is proposed to determine the required lap-splice length in RC beams using a multilayer genetic programming machine learning (MLGPML) algorithm. This model was obtained from the study of the bond stress between concrete with normal and high compressive strength and tensile reinforcement. Previous models were used to estimate this bond stress, taking into account different parameters. In this study, using the results of 386 experimental tests on reinforced concrete beams, the lap-splice length and the required transverse reinforcement over that length were calculated. The proposed model to determine the bond stress is very well suited to the design purposes by comparison with various experimental campaigns’ results.
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