Size Dependent Prediction of Ultimate Shear Strength of RC Deep Beams Using Refined Strut-And-Tie Model

ABOUT THE INTERNATIONAL CONCRETE ABSTRACTS PORTAL

  • The International Concrete Abstracts Portal is an ACI led collaboration with leading technical organizations from within the international concrete industry and offers the most comprehensive collection of published concrete abstracts.

International Concrete Abstracts Portal

  


Title: Size Dependent Prediction of Ultimate Shear Strength of RC Deep Beams Using Refined Strut-And-Tie Model

Author(s): G. Appa Rao and R. Sundaresan

Publication: Special Publication

Volume: 300

Issue:

Appears on pages(s): 1-26

Keywords: Deep Beam, Shear Strength, Strut-and-Tie Model, Size Effect, Reinforced Concrete

Date: 3/11/2015

Abstract:
Behavior of RC deep beams is very complex, and several factors influence its shear strength. This paper discusses on analytical investigations on the shear strength of reinforced concrete (RC) deep beams. An expression for estimating the ultimate shear strength of RC deep beams provided with shear reinforcement, considering the beam depth including all other influencing parameters has been developed. The proposed ultimate shear strength estimation also considers the shear transfer mechanism of RC deep beams through a refined strut-and-tie model retaining the generic form of the modified Bazant’s size effect law, using a large selected experimental data base. The shear strength of RC deep beams has been predicted accurately using the square root of beam depth. The proposed size dependent equation is simple and accurate for RC deep beams with a/d ratio less than 2.0. Various parameters such as strut angle, flexural reinforcement ratio, shear reinforcement, both vertical and horizontal and beam depth have been accurately accommodated in the present size dependent shear strength expression using refined strut-andtie model. The prediction of the shear strength of RC deep beams has been observed to be reasonably agreeable with the experimental observations.