Proposed numerical and machine learning models for fiber-reinforced polymer concrete-steel hollow and solid elliptical columns  

作　　者：Tang QIONG Ishan JHA Alireza BAHRAMI Haytham F.ISLEEM Rakesh KUMAR Pijush SAMUI 

机构地区：[1]School of Applied Technologies,Qujing Normal University,Qujing 655011,China [2]Department of Civil Engineering,Indian Institute of Technology-BHU,Varanasi 221005,India [3]Department of Building Engineering,Energy Systems and Sustainability Science,Faculty of Engineering and Sustainable Development,University of Gävle,Gävle 80176,Sweden [4]Department of Civil Engineering,National Institute of Technology-Patna,Patna 800005,India

出　　处：《Frontiers of Structural and Civil Engineering》2024年第8期1169-1194,共26页结构与土木工程前沿（英文版）

基　　金：Qujing Normal University Student Innovation and Entrepreneurship Training Project,No.S202310684035.

摘　　要：This study employs a hybrid approach,integrating finite element method(FEM)simulations with machine learning(ML)techniques to investigate the structural performance of double-skin tubular columns(DSTCs)reinforced with glass fiber-reinforced polymer(GFRP).The investigation involves a comprehensive examination of critical parameters,including aspect ratio,concrete strength,number of GFRP confinement layers,and dimensions of steel tubes used in DSTCs,through comparative analyses and parametric studies.To ensure the credibility of the findings,the results are rigorously validated against experimental data,establishing the precision and trustworthiness of the analysis.The present research work examines the use of the columns with elliptical cross-sections and contributes valuable insights into the application of FEM and ML in the design and evaluation of structural systems within the field of structural engineering.

关 键 词：elliptical column fiber-reinforced polymer machine learning finite element method ABAQUS 

分 类 号：TU528[建筑科学—建筑技术科学]