A Simplified Empirical Model for Predicting Residual Flexural Capacity of Corroded Prestressed Concrete Beams

Prestressed concrete (PSC) beams are widely used in critical infrastructure but are highly susceptible to corrosion in aggressive environments, which can significantly compromise their structural performance. Accurate prediction of residual flexural capacity is crucial for evaluating the safety and serviceability of corroded PSC elements. This study presents a simplified empirical model for estimating the residual flexural strength of corroded PSC beams, with maximum strand mass loss serving as the key governing parameter. This approach is superior to existing models, which typically rely on average mass loss and fail to capture the localized stress concentrations induced by pitting corrosion. The model was developed from an experimental dataset of 31 corroded beams, covering maximum mass loss up to 90% using exponential regression. An extensive database of 124 test results from 19 independent studies was used for the purpose of verification and comparison with existing models. The proposed model was capable of effectively capturing the degradation trend and providing accurate and conservative predictions, with an average experimental-to-calculated capacity ratio of 1.04 and a coefficient of variation of 8.7%. Its direct reliance on maximum mass loss, which can be indirectly inferred from corrosion-induced crack widths, significantly enhances the practicality and safety of the model for field condition assessments and life-cycle management of PSC structures.

Authors

Institutions

Publication Details

Journal
Buildings
Published
2025-11-27
DOI
https://doi.org/10.3390/buildings15234310
Primary Topic
Concrete Corrosion and Durability
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Simplified Empirical Model for Predicting Residual Flexural Capacity of Corroded Prestressed Concrete Beams

Ahmed Kamal El-Sayed, Abdulaziz I. Al‐Negheimish, Mshtaq Ahmed, Abdulrahman M. Alhozaimy
Buildings
Concrete Corrosion and Durability
article

A Simplified Empirical Model for Predicting Residual Flexural Capacity of Corroded Prestressed Concrete Beams

Ahmed Kamal El-Sayed, Abdulaziz I. Al‐Negheimish, Mshtaq Ahmed, Abdulrahman M. Alhozaimy
article en

Abstract

Prestressed concrete (PSC) beams are widely used in critical infrastructure but are highly susceptible to corrosion in aggressive environments, which can significantly compromise their structural performance. Accurate prediction of residual flexural capacity is crucial for evaluating the safety and serviceability of corroded PSC elements. This study presents a simplified empirical model for estimating the residual flexural strength of corroded PSC beams, with maximum strand mass loss serving as the key governing parameter. This approach is superior to existing models, which typically rely on average mass loss and fail to capture the localized stress concentrations induced by pitting corrosion. The model was developed from an experimental dataset of 31 corroded beams, covering maximum mass loss up to 90% using exponential regression. An extensive database of 124 test results from 19 independent studies was used for the purpose of verification and comparison with existing models. The proposed model was capable of effectively capturing the degradation trend and providing accurate and conservative predictions, with an average experimental-to-calculated capacity ratio of 1.04 and a coefficient of variation of 8.7%. Its direct reliance on maximum mass loss, which can be indirectly inferred from corrosion-induced crack widths, significantly enhances the practicality and safety of the model for field condition assessments and life-cycle management of PSC structures.

BuildingsVol. 15(23)
King Saud University (SA)
King Saud University
Openalex Percentile: Top 62%
Concrete Corrosion and Durability
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.