Axial compressive behavior of circular concrete-filled double steel tubular short columns

被引：22
作者：
Ci, Junchang [1 ]
Ahmed, Mizan [2 ,3 ]
Viet-Linh Tran [4 ]
Jia, Hong [5 ]
Chen, Shicai [6 ]
机构：
[1] Beijing Univ Technol, Coll Architecture & Civil Engn, Beijing, Peoples R China
[2] Univ Wollongong, Sch Civil Min & Environm Engn, Northfields Ave, Wollongong, NSW 2522, Australia
[3] Monash Univ, Dept Architecture, Melbourne, Vic, Australia
[4] Vinh Univ, Dept Civil Engn, Vinh, Vietnam
[5] CRCC Dev Grp Co Ltd, Beijing, Peoples R China
[6] Beijing Univ Technol, Key Lab Urban Secur & Disaster Engn, Minist Educ, Beijing, Peoples R China
来源：
ADVANCES IN STRUCTURAL ENGINEERING | 2022年 / 25卷 / 02期
关键词：
CFDST columns; composite columns; short columns; compressive strengths; artificial neural network; STRESS-STRAIN MODEL; NONLINEAR-ANALYSIS; STUB COLUMNS; NUMERICAL-ANALYSIS; CONFINED CONCRETE; STRENGTH; TUBE; CAPACITY; PERFORMANCE; PREDICTION;
D O I：
10.1177/13694332211046345
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
This article investigates the axial compressive performance of concrete-filled double steel tubular (CFDST) short columns composed of circular section loaded concentrically. An experimental program comprised of compression tests on short columns is carried out to examine their structural performance. Axial compression tests on conventional concrete-filled steel tubular (CFST) columns and double-skin concrete-filled steel tubular (DCFST) columns are also performed for comparison purposes. The test parameters include the diameter-to-thickness of the outer and inner steel tubes, concrete strength, and diameter ratio. The test results exhibit that CFDST short columns composed of the circular section have improved structural performance compared to its CFST and DCFST counterparts. A theoretical model is also presented to simulate the test ultimate strengths and load-axial strain relationships of CFDST columns. The existing design models proposed including the codified design specifications are evaluated against the collected test data for predicting the axial compressive strengths of circular CFDST columns. It is seen that the existing codified design models cannot yield their ultimate axial compressive strengths accurately. A practical artificial neural network (ANN) model is proposed to estimate the ultimate load of such columns loaded concentrically.
引用
收藏
页码：259 / 276
页数：18
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