TY - JOUR
T1 - Axial load-carrying capacity of concrete-filled steel tube columns
T2 - a comparative analysis of various modeling techniques
AU - Abdellatif, Selmi
AU - Raza, Ali
AU - Alsulamy, Saleh
AU - Khadimallah, Mohamed Amine
N1 - Publisher Copyright:
© 2023 Taylor & Francis Group, LLC.
PY - 2024
Y1 - 2024
N2 - Limited research is available in the literature to investigate the presentation of normal strength concrete-filled steel tube (CFST) circular compression elements under compression loading by considering various material and geometric coefficients. Thus, the present study investigates the mechanical behavior of CFST compression elements employing nonlinear finite element analysis (NLFEA), empirical/theoretical modeling, and a newly developed Artificial Neural Network (ANN) model, based on a large experimental database of 1223 samples. The NLFEA modeling is performed in ABAQUS (6.14) with an improved concrete damaged plasticity model for laterally restrained concrete. Various geometric and material properties are considered, for parametric NLFEA estimates preliminary validated toward the available experimental database. A new ANN model for the load-carrying capacity of CFST circular elements was also offered by employing the experimental database. The comparison between the calculations of the NLFEA model, empirical model, and ANN model displayed a close agreement with the database results.
AB - Limited research is available in the literature to investigate the presentation of normal strength concrete-filled steel tube (CFST) circular compression elements under compression loading by considering various material and geometric coefficients. Thus, the present study investigates the mechanical behavior of CFST compression elements employing nonlinear finite element analysis (NLFEA), empirical/theoretical modeling, and a newly developed Artificial Neural Network (ANN) model, based on a large experimental database of 1223 samples. The NLFEA modeling is performed in ABAQUS (6.14) with an improved concrete damaged plasticity model for laterally restrained concrete. Various geometric and material properties are considered, for parametric NLFEA estimates preliminary validated toward the available experimental database. A new ANN model for the load-carrying capacity of CFST circular elements was also offered by employing the experimental database. The comparison between the calculations of the NLFEA model, empirical model, and ANN model displayed a close agreement with the database results.
KW - Concrete-filled steel tube (CFST) circular compression elements
KW - artificial neural network (ANN) model
KW - axial load-carrying (LCC) capacity
KW - finite element numerical model
KW - theoretical model
UR - https://www.scopus.com/pages/publications/85152368328
U2 - 10.1080/15376494.2023.2188325
DO - 10.1080/15376494.2023.2188325
M3 - Article
AN - SCOPUS:85152368328
SN - 1537-6494
VL - 31
SP - 3980
EP - 4002
JO - Mechanics of Advanced Materials and Structures
JF - Mechanics of Advanced Materials and Structures
IS - 17
ER -