Dataset for Cyclic Nonlinear Numerical Modelling of Corroded Reinforced Concrete Columns and Frames

Corrosion of reinforcing steel is a key cause of deterioration in reinforced concrete (RC) structures exposed to coastal environments with chloride presence. The loss of reinforcing steel cross-sectional area, cracking of the concrete cover, and reduction in confinement progressively decrease both strength and ductility of structural elements. This study provides a reproducible, open-access dataset, compiling input parameters and numerical results of the cyclic behaviour of isolated RC columns and RC frames, specifically addressing their nonlinear cyclic response under moderate corrosion (η < 25%), as well as in the non-corroded (baseline) conditions, generated through conventional nonlinear modelling. In terms of modelling, the methodology applies fibre-section modelling for columns and concentrated plastic hinges for beams. Furthermore, the corrosion effects are incorporated by reducing the steel area and ultimate strain, while also accounting for the decrease in compressive strength of the cracked concrete cover. Therefore, the cyclic response is represented by a Pivot-type hysteretic model. It is worth noting that the dataset provides model input information, such as material stress–strain relationships and backbone curves reflecting corrosion-induced deterioration. It also includes structural outputs, such as force–displacement relationships, and envelopes of quasi-static hysteretic cycles for the analyzed columns and frames. Overall, the dataset facilitates the calibration and validation of numerical models for RC structures affected by corrosion. In conclusion, the contribution enhances the reliability of computational simulations and supports the development of predictive tools for structural performance under degradation scenarios.

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Published
2026-04-25
DOI
https://doi.org/10.3390/data11050094
Primary Topic
Concrete Corrosion and Durability
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article
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article

Dataset for Cyclic Nonlinear Numerical Modelling of Corroded Reinforced Concrete Columns and Frames

Sergio Márquez-Domínguez, Gustavo Delgado Reyes, Dariniel Barrera-Jiménez, Irving Ramírez-González et al.
Data
Concrete Corrosion and Durability
article

Dataset for Cyclic Nonlinear Numerical Modelling of Corroded Reinforced Concrete Columns and Frames

Sergio Márquez-Domínguez, Gustavo Delgado Reyes, Dariniel Barrera-Jiménez, Irving Ramírez-González, José Piña-Flores, Rolando Salgado-Estrada, Armando Aguilar-Menéndez, Alejandro Vargas-Colorado, José Barradas-Hernández, Franco Carpio-Santamaría
article en

Abstract

Corrosion of reinforcing steel is a key cause of deterioration in reinforced concrete (RC) structures exposed to coastal environments with chloride presence. The loss of reinforcing steel cross-sectional area, cracking of the concrete cover, and reduction in confinement progressively decrease both strength and ductility of structural elements. This study provides a reproducible, open-access dataset, compiling input parameters and numerical results of the cyclic behaviour of isolated RC columns and RC frames, specifically addressing their nonlinear cyclic response under moderate corrosion (η < 25%), as well as in the non-corroded (baseline) conditions, generated through conventional nonlinear modelling. In terms of modelling, the methodology applies fibre-section modelling for columns and concentrated plastic hinges for beams. Furthermore, the corrosion effects are incorporated by reducing the steel area and ultimate strain, while also accounting for the decrease in compressive strength of the cracked concrete cover. Therefore, the cyclic response is represented by a Pivot-type hysteretic model. It is worth noting that the dataset provides model input information, such as material stress–strain relationships and backbone curves reflecting corrosion-induced deterioration. It also includes structural outputs, such as force–displacement relationships, and envelopes of quasi-static hysteretic cycles for the analyzed columns and frames. Overall, the dataset facilitates the calibration and validation of numerical models for RC structures affected by corrosion. In conclusion, the contribution enhances the reliability of computational simulations and supports the development of predictive tools for structural performance under degradation scenarios.

DataVol. 11(5)
Universidad Veracruzana (MX)
Life below water
Openalex Percentile: Top 10%
Concrete Corrosion and Durability
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