Multiple linear regression models for shear strength prediction and design of simplysupported deep beams subjected to symmetrical point loads

Abstract

Because of nonlinear strain distributions caused either by abrupt changes in geometry or in loading in deep beam, the approach for conventional beams is not applicable. Consequently, strut-and-tie model (STM) has been applied as the most rational and simple method for strength prediction and design of reinforced concrete deep beams. A deep beam is idealized by the STM as a truss-like structure consisting of diagonal concrete struts and tension ties. There have been numerous works proposing the STMs for deep beams. However, uncertainty and complexity in shear strength computations of deep beams can be found in some STMs. Therefore, improvement of methods for predicting the shear strengths of deep beams are still needed. By means of a large experimental database of 406 deep beam test results covering a wide range of influencing parameters, several shapes and geometry of STM and six state-of-the-art formulation of the efficiency factors found in the design codes and literature, the new STMs for predicting the shear strength of simply supported reinforced concrete deep beams using multiple linear regression analysis is proposed in this paper. Furthermore, the regression diagnostics and the validation process are included in this study. Finally, two numerical examples are also provided for illustration.

Keywords

• Deep beam
• Efficiency factor
• Multiple regression
• Strut-and-tie model