Computers and Concrete

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Fiber reinforced concrete corbels: Modeling shear strength via symbolic regression

  • Received : 2016.10.26
  • Accepted : 2017.03.21
  • Published : 2017.07.25
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Abstract

In this study, a novel application of symbolic regression (SR) is employed for the prediction of ultimate shear strength of steel fiber reinforced (SFRC) and glass fiber reinforced (GFRC) corbels without stirrups, for the first time in the literature. A database is created using the test results (42 tests) conducted by the authors of current paper as well as the previous studies available in the literature. A symbolic regression based empirical formulation is proposed using this database. The formulation is unique in a way that it has the capability to predict the shear strength of both SFRC and GFRC corbels. The performance of proposed model is tested against randomly selected testing set. Additionally, a parametric study with a wide range of variables is carried out to test the effect of each parameter on the shear strength. The results confirm the high prediction capacity of proposed model.

Keywords

Acknowledgement

Grant : MF.12.13-Modeling of Inelastic Behavior of Structures by Soft Computing Techniques

Supported by : Gaziantep University

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