Data-Driven Predictive Formulation for FRP-Confined Circular Concrete Columns

This study presents a new design-oriented, regression-based model for predicting the ultimate compressive strength of circular concrete columns confined with fiber-reinforced polymer (FRP) jackets. The model is grounded in fundamental confinement mechanics and accounts for key parameters, including FRP elastic modulus, ultimate tensile strain, confinement stiffness, unconfined concrete strength, and column diameter. A comprehensive and rigorously filtered experimental database comprising ۱,۳۷۶ FRP-confined circular concrete specimens was assembled, covering concrete strengths from ۶.۶ to ۲۰۴ MPa and FRP types including CFRP, GFRP, BFRP, and AFRP. A carefully curated experimental database of ۱,۳۷۶ circular FRP-confined specimens was assembled, covering a broad spectrum of concrete strengths and FRP types. Regression analysis was used to calibrate the model, and a dimension-based correction factor was incorporated to capture the influence of cross-sectional geometry. The resulting formulation demonstrates robust predictive capability and general applicability across diverse concrete strengths and column geometries, providing a reliable tool for practical engineering design. Parametric studies further illustrate how confinement efficiency varies with concrete strength and FRP properties, offering guidance for optimizing FRP confinement in practice.

Keywords:

FRP confinement , Compressive strength , Predictive model , Design-oriented model , Confined concrete