Concepts and Functions in the Building Engineering

Concepts and Functions in the Building Engineering

Regression Analysis of NSM FRP and FRP Wrapping Effects in Strengthened RC Columns

Document Type : مقاله پژوهشی

Authors
Mohsen Ali Shayanfar
Solmaz Afzali
Mohammad Ghanooni-Bagha
Professor, School of Civil Engineering, Iran University of Science and Technology, Narmak, Tehran 16846, Iran
Abstract
In this study, a simple regression-based approach is developed to accurately predict the axial load capacity of RC (Reinforced Concrete) columns strengthened using NSM (Near Surface Mounted) and hybrid FRP (Fiber Reinforced Polymer) methods. The model is trained and validated using a dataset of 112 experimentally tested specimens collected from the literature, including 22 data points from the authors' previous study and 90 additional cases. Key input parameters include column dimensions (width and height), concrete compressive strength (mean 35.1 MPa), longitudinal steel ratio (mean 1.43%), transverse steel ratio, number and properties of NSM FRP and FRP jackets, and load eccentricity ratio (mean 0.18). The dataset was split into 80% training and 20% test sets. Three regression models were developed: (i) full linear regression, (ii) regression with statistically significant features, and (iii) stepwise regression. The stepwise regression model showed the best performance with a Mean Absolute Percentage Error (MAPE) of 10.85% and Root Mean Square Error (RMSE) of 201.91 kN on the test set. This approach eliminates complex trial-and-error procedures and offers a transparent, practical tool for engineers and researchers involved in strengthening RC columns.
Keywords
RC Column, NSM FRP, FRP jacket, Axial Strengthening
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Afzali, S., Afzali, S.A.E., Shayanfar, M.A., Ghanooni-bagha, M. and Afzali, M., 2025. Predictive Models for the Axial Capacity of NSM-and Hybrid FRP-Strengthened RC Columns Using Ensemble Learning Optimized by Metaheuristic Algorithms. Case Studies in Construction Materials, p.e05167