A Combined Numerical and Experimental Evaluation of the Flexural Performance of Wire Mesh-Strengthened RC Beam

The focus of this study is to determine how well stainless-steel wire mesh (SSWM), an externally bonded strengthening material, may improve the flexural performance of reinforced concrete (RC) beams. Evaluating the structural advantages of SSWM in terms of load-carrying capacity, deflection reduction, and crack management is the main goal. The use of SSWM as an affordable, long-lasting, and fire-resistant reinforcing method for RC beams is what makes this work novel. Finite element analysis (FEA) was carried out using Abaqus to validate the results of experimental testing on strengthened and control beams, as part of a combined experimental and numerical approach. The results show that, in comparison to control beams, SSWM greatly enhances flexural performance, increasing load capacities by 99% to 149%. Furthermore, mid-span deflections decreased from 53.7% to 53%, indicating improved structural stability. According to the crack study, reinforced beams had better damage control, fewer cracks, and the capacity to support loads after they first cracked. The accuracy of FEA in predicting the structural behavior of SSWM-strengthened beams was confirmed by the close match between the numerical models and experimental data. This study provides a promising and sustainable strengthening solution for RC structures, offering both economic and environmental benefits.

Institutions

Publication Details

Journal
passer
Published
2025-06-20
DOI
https://doi.org/10.24271/psr.2025.497536.1881
Primary Topic
Structural Behavior of Reinforced Concrete
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Combined Numerical and Experimental Evaluation of the Flexural Performance of Wire Mesh-Strengthened RC Beam

passer
Structural Behavior of Reinforced Concrete
article

A Combined Numerical and Experimental Evaluation of the Flexural Performance of Wire Mesh-Strengthened RC Beam

article en

Abstract

The focus of this study is to determine how well stainless-steel wire mesh (SSWM), an externally bonded strengthening material, may improve the flexural performance of reinforced concrete (RC) beams. Evaluating the structural advantages of SSWM in terms of load-carrying capacity, deflection reduction, and crack management is the main goal. The use of SSWM as an affordable, long-lasting, and fire-resistant reinforcing method for RC beams is what makes this work novel. Finite element analysis (FEA) was carried out using Abaqus to validate the results of experimental testing on strengthened and control beams, as part of a combined experimental and numerical approach. The results show that, in comparison to control beams, SSWM greatly enhances flexural performance, increasing load capacities by 99% to 149%. Furthermore, mid-span deflections decreased from 53.7% to 53%, indicating improved structural stability. According to the crack study, reinforced beams had better damage control, fewer cracks, and the capacity to support loads after they first cracked. The accuracy of FEA in predicting the structural behavior of SSWM-strengthened beams was confirmed by the close match between the numerical models and experimental data. This study provides a promising and sustainable strengthening solution for RC structures, offering both economic and environmental benefits.

passerVol. 7
Kurdistan Regional Government (IQ), Sulaimani Polytechnic University (IQ), University of Garmian
Affordable and clean energy
Openalex Percentile: Top 84%
Structural Behavior of Reinforced Concrete
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.