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Evaluation of Residual Strength of Corroded Reinforced Concrete Beams Using Machine Learning Models

  • Research Article-Computer Engineering and Computer Science
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Abstract

One of the main causes of structural durability degradation of reinforced concrete structures is corrosion of reinforcing bars. Predicting the bearing capacity of corroded reinforced concrete beams has been examined from experimental and theoretical perspectives. Most of the research works have been done on using individual predicting models instead of exploring the capacity of ensemble models. This study employs various machine-learning models, including support vector regression, artificial neural network, generalized linear regression, classification and regression-based techniques, exhaustive Chi-squared automatic interaction detection, and ensemble inference models to predict the residual capacity of corroded reinforced concrete beams based on actual data. A dataset of 120 samples collected in Ho Chi Minh City, Vietnam, is used for constructing, validating, testing the proposed models. The experimental results and statistical tests show that the generalized linear regression is the best model among all considered single predictive models and the ensemble model of generalized linear regression and artificial neural network obtained the highest prediction performance in estimating residual strength. The contribution to the body of knowledge is the development of ensemble models and various individual models that can predict the residual capacity of corroded reinforced concrete beams in a short time. This study demonstrates an effective prediction application for early structural durability estimation in the planning of building maintenance.

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Acknowledgements

This work belongs to the project grant No: T2021-98TĐ funded by Ho Chi Minh City University of Technology and Education, Vietnam.

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Authors and Affiliations

  1. Department of Civil Engineering, Ho Chi Minh City University of Technology and Education, Ho Chi Minh City, Vietnam

    Thanh-Hung Nguyen

  2. Faculty of Civil Engineering, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Vietnam

    Dang-Trinh Nguyen & Duc-Hoc Tran

  3. Vietnam National University Ho Chi Minh City, Linh Trung Ward, Thu Duc District, Ho Chi Minh City, 700000, Vietnam

    Dang-Trinh Nguyen & Duc-Hoc Tran

  4. Department of Civil Engineering, International University, Vietnam National University HCMC, Ho Chi Minh City, Vietnam

    Dinh-Hung Nguyen

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  1. Thanh-Hung Nguyen
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  4. Duc-Hoc Tran
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Correspondence to Dang-Trinh Nguyen.

Appendix: Supplementary Data

Appendix: Supplementary Data

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Table 5 Details of 120 data
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Nguyen, TH., Nguyen, DT., Nguyen, DH. et al. Evaluation of Residual Strength of Corroded Reinforced Concrete Beams Using Machine Learning Models. Arab J Sci Eng 47, 9985–10002 (2022). https://doi.org/10.1007/s13369-021-06493-8

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