ORIGINAL RESEARCH article
Front. Built Environ.
Sec. Computational Methods in Structural Engineering
Volume 11 - 2025 | doi: 10.3389/fbuil.2025.1693218
Stacked ensemble and SHAP-based approach for predicting plastic rotational capacity in RC columns
Provisionally accepted- Universitatea Tehnica de Constructii Bucuresti, Bucharest, Romania
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The accurate estimation of plastic rotational capacity in reinforced concrete (RC) elements is essential for performance-based seismic design and structural safety assessments. In this study, an extensive experimental database, comprising 258 rectangular and 151 circular RC column specimens, was compiled based on open data available and used to train machine learning models for predicting this parameter. Three algorithms, i.e. Support Vector Regression (SVR), Random Forest (RF), and Extreme Gradient Boosting (XGBoost), were implemented and optimized using grid search within a nested cross-validation framework. The predictive performance was evaluated by averaging the coefficient of determination (R²) across five outer folds, while final accuracy was assessed on the test set using both R² and the Mean Absolute Error (MAE). Model interpretability was improved using SHAP (SHapley Additive exPlanations) analysis, which quantified the influence of input parameters on predictions. Finally, a stacking ensemble model was developed to integrate the strengths of the individual regressors. The proposed methodology demonstrates increased accuracy and robustness in predicting the plastic rotational capacity of both circular and rectangular RC columns, providing a valuable tool for seismic assessment and structural reliability analysis.
Keywords: reinforced concrete structures, Plastic rotation capacity, machine learning, Stacked ensemble, SHAP (SHapley Additive exPlanations), ensemble learning
Received: 26 Aug 2025; Accepted: 22 Sep 2025.
Copyright: © 2025 Kadhim, Craifaleanu and Lozinca. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Iolanda-Gabriela Craifaleanu, iolanda.craifaleanu@utcb.ro
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