Symbolic Regression Model for Predicting Compression Strength of Prismatic Masonry Columns Confined by FRP

Author:

Alotaibi Khalid Saqer1ORCID,Islam A. B. M. Saiful1ORCID

Affiliation:

1. Department of Civil and Construction Engineering, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam 31451, Saudi Arabia

Abstract

The use of Fiber Reinforced Polymer (FRP) materials for the external confinement of existing concrete or masonry members is now an established technical solution. Several studies in the scientific literature show how FRP wrapping can improve the mechanical properties of members. Though there are numerous methods for determining the compressive strength of FRP confined concrete, no generalized formulae are available because of the greater complexity and heterogeneity of FRP-confined masonry. There are two main objectives in this analytical study: (a) proposing an entirely new mathematical expression to estimate the compressive strength of FRP confined masonry columns using symbolic regression model approach which can outperform traditional regression models, and (b) evaluating existing formulas. Over 198 tests of FRP wrapped masonry were compiled in a database and used to train the model. Several formulations from the published literature and international guidelines have been compared against experimental data. It is observed that the proposed symbolic regression model shows excellent performance compared to the existing models. The model is easier, has no restriction and thereby it can be feasibly employed to foresee the behavior of FRP confined masonry elements. The coefficient of determination for the proposed symbolic regression model is determined as 0.91.

Publisher

MDPI AG

Subject

Building and Construction,Civil and Structural Engineering,Architecture

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3