Design‐oriented approach to predict shear strength of reinforced concrete beams. (25th September 2017)

• Record Type: Journal Article
• Authors: Baghi, Hadi; Barros, Joaquim A. O.
• Other Names: Muttoni Aurelio guestEditor.
• Is Part Of: Structural concrete. Volume 19:Number 1(2018)
• Page Start: 98
• Page End: 115
• Publication Date: 2017-09-25
• Subjects: Monte Carlo simulation -- reinforced concrete beams -- sensitivity analysis -- shear strength -- simplified modified compression field theory -- T cross section beams; Reinforced concrete -- Periodicals; 624.1834
• DOI: 10.1002/suco.201700095
• Languages: English
• ISSNs: 1464-4177

Abstract

Abstract : There are different approaches to predict the shear strength of reinforced concrete (RC) beams, but their predictive performance is still relatively low due to several and complex resisting mechanisms involved in shear. In addition, most of design approaches ignore the influence of the flange of T cross section beams on the ultimate shear capacity. This paper aims to present a design‐oriented approach to predict the load carrying capacity of RC beams failing in shear. This approach is based on the simplified modified compression field theory (SMCFT). A sensitivity analysis is carried out to assess the importance of the input parameters that mostly affect the shear strength of RC members. Taking into account the results of the sensitivity analysis, two simple equations are proposed for obtaining the: (a) tensile stress factor in the cracked concrete ( β ) and (b) inclination of the diagonal compressive stress in the web of the section ( θ ). The obtained equations eliminate the iterative process required by the SMCFT and provide a straightforward design methodology to find β and θ with suitable accuracy for design purposes. In addition, a coefficient is presented to take into account the effect of the flange on the shear capacity of T shaped cross section beams. To appraise the predictive performance of the new approach, a database is set. By evaluating the ratio between the experimental results and the analytical predictions, an average value of 1.24 with a coefficient of variation of 20.9% is obtained.