Predicting shear strength in reinforced concrete deep beams through finite element modeling of diverse concrete materials
Year: 2025
Type: article
Abstract: This study investigates the prediction of the strength of reinforced concrete deep beams, critical components in urban infrastructure, by evaluating their load-carrying capacities through finite element modeling and nonlinear inelastic analyses using LS-DYNA software. Four widely used concrete material models were examined: Mat084/085, Mat159, Mat072R3, and Mat016. Analyses were conducted on two single-span and four double-span beams with varying reinforcement configurations and an aspect ratio of 1.0, based on well-documented experimental setups. Comparative analyses of force-displacement behavior and stress distributions revealed significant differences in shear strength predictions across the models, with Mat159 providing the most accurate results. These findings establish a reliable and cost-effective approach for predicting the capacities of deep beams, reducing reliance on extensive experimental testing. The study contributes valuable insights for improving strength predictions in critical infrastructure applications such as bridges and foundations.
Authors: Erkan Polat, Gökhan Karaman
Institution: Munzur University
Language: English
Subfield: Building and Construction
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4408153107