Strut-and-tie models (STMs) are often used for the design of shear critical deep members
because they can rationalize the shear transfer within discontinuous or disturbed regions in …

This study aims to predict the shear strength of reinforced concrete (RC) deep beams based
on artificial neural network (ANN) using four training algorithms, namely, Levenberg …

Reinforced Concrete (RC) deep beams perform better structurally when steel fibers are
added, as this reduces the need for web steel reinforcements, boosts shear strength, and …

This paper investigates the flexural shear behaviour of reinforced beams made from different
Crumbed Rubber Concrete (CRC) mixes having similar compressive strength and different …

In this study, an experimental study is performed to investigate the effects of section height
(h), ratio of shear span to effective depth (a/d) and compressive strength of concrete (f c') …

In this study, the neural network model for predicting shear capacity of reinforced concrete
(RC) beams without shear reinforcements is developed. Several explanatory variables …

In this present study a comprehensive literature has been reviewed on shear strength of
deep beams. The shear behavior of deep beams must be understood by varying various …

Geopolymer concrete (GPC) has emerged as a sustainable alternative to ordinary Portland
cement concrete (OPCC) as GPC significantly reduces embodied carbon dioxide emissions …

Shear strength prediction for reinforced concrete (RC) beams is a complex non-linear
problem impacted by many factors. Traditional Machine Learning (ML) models for shear …

Prior studies point to high model uncertainty in shear prediction. Model factors for various
shear prediction models are characterized here, based on a recent and well‐vetted …