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 

作者机构：School of Applied TechnologiesQujing Normal UniversityQujing 655011China Department of Civil EngineeringIndian Institute of Technology-BHUVaranasi 221005India Department of Building EngineeringEnergy Systems and Sustainability ScienceFaculty of Engineering and Sustainable DevelopmentUniversity of GävleGävle 80176Sweden Department of Civil EngineeringNational Institute of Technology-PatnaPatna 800005India 

出 版 物：《Frontiers of Structural and Civil Engineering》 (结构与土木工程前沿（英文版）)

年 卷 期：2024年第18卷第8期

页      面：1169-1194页

核心收录：

学科分类：08[工学] 081304[工学-建筑技术科学] 0805[工学-材料科学与工程（可授工学、理学学位）] 080502[工学-材料学] 0813[工学-建筑学] 

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

主　　题：elliptical column fiber-reinforced polymer machine learning finite element method ABAQUS 

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 *** ensure the credibility of the findings,the results are rigorously validated against experimental data,establishing the precision and trustworthiness of 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.