Axial load-carrying capacity of concrete-filled steel tube columns: a comparative analysis of various modeling techniques

Selmi Abdellatif, Ali Raza, Saleh Alsulamy, Mohamed Amine Khadimallah

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)3980-4002
Number of pages23
JournalMechanics of Advanced Materials and Structures
Volume31
Issue number17
DOIs
StatePublished - 2024

Keywords

  • Concrete-filled steel tube (CFST) circular compression elements
  • artificial neural network (ANN) model
  • axial load-carrying (LCC) capacity
  • finite element numerical model
  • theoretical model

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