Machine Learning-Based Prediction of Compressive Performance in Circular Concrete Columns Confined with FRP
Dhakal, N., Abbas, A., Ahmed, H. and Sharif, S. 2023. Machine Learning-Based Prediction of Compressive Performance in Circular Concrete Columns Confined with FRP. 3ICT 2023: International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies. University of Bahrain, Bahrain 20 - 21 Nov 2023 IEEE.
|Authors||Dhakal, N., Abbas, A., Ahmed, H. and Sharif, S.|
This article presents a comprehensive investigation, focusing on the prediction and formulation of the design equation of compressive strength of circular concrete columns confined with Fiber Reinforced Polymer (FRP) using advanced machine learning models. Through an extensive analysis of 170 experimental data specimens, the study examines the effects of six key parameters, including concrete cylinder diameter, concrete cylinder-FRP thickness, compressive strength of concrete without FRP, initial compressive strain of concrete without FRP, elastic modulus and tensile strength of FRP, on the compressive strength of the circular concrete columns confined with FRP. The predictive model and design equation of compressive strength is developed using a machine learning technique, specifically the artificial neural networks (ANN) model. The results demonstrates strong correlations between the compressive strength of the circular concrete columns confined with FRP and certain factors, such as the compressive strength of the concrete and compressive strain of the concrete column without FRP, elastic modulus of FRP, and tensile strength of FRP. The ANN model specifically developed using Neural Designer, exhibits superior predictive accuracy compared to other constitutive models, showcasing its potential for practical implementation. The study's findings contribute valuable insights into accurately predicting the compressive performance of circular concrete columns confined with FRP, which can aid in optimizing and designing civil engineering structures for enhanced performance and efficiency.
|Conference||3ICT 2023: International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies|
|Accepted author manuscript|
File Access Level
|Publication process dates|
|Accepted||14 Sep 2023|
|Deposited||25 Sep 2023|
|Journal citation||In Press|
|Copyright holder||© 2023, IEEE|
|Copyright information||Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.|
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