ColumnsNet: Neural Network Model for Constructing Interaction Diagrams and Slenderness Limit for FRP-RC Columns
Publication: Journal of Structural Engineering
Volume 148, Issue 8
Abstract
Predicting the axial capacity and behavior of concentrically, eccentrically, and slender loaded fiber-reinforced polymer (FRP)-RC columns is not completely established, and the current design codes lack design provisions for FRP-RC columns. Rather, it requires ignoring the contribution of FRP bars in compression conservatively. To bridge this knowledge gap, this study proposes an artificial neural network (ANN)-based model capable of predicting the axial capacity and slenderness limit and constructing an interaction diagram for FRP-reinforced columns. The aforementioned model was trained with Bayesian regularization utilizing a comprehensive database of 241 tested FRP-RC columns. Parameters included in the model are column cross-sectional area, compressive strength, FRP elastic modulus, reinforcement ratio, eccentricity ratio, and slenderness ratio. The predictions of the ANN-based model match well with the experimental results of the compiled database; the model predictions have a COV of 15% and root-mean square error of 130 kN. In addition, a parametric study was conducted to investigate the effect of parameters and ensure the generalizability of the proposed model.
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Data Availability Statement
Data supporting the findings of this study are available in the article and from the corresponding author upon reasonable request.
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Received: Sep 20, 2021
Accepted: Mar 2, 2022
Published online: May 19, 2022
Published in print: Aug 1, 2022
Discussion open until: Oct 19, 2022
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