Compressive behavior of elliptical concrete-filled steel tubular short columns using numerical investigation and machine learning techniques.

ABSTRACT: This paper presents a non-linear finite element model (FEM) to predict the load-carrying capacity of three different configurations of elliptical concrete-filled steel tubular (CFST) short columns: double steel tubes with sandwich concrete (CFDST), double steel tubes with sandwich concrete and concrete inside the inner steel tube, and a single outer steel tube with sandwich concrete. Then, a parametric and analytical study was performed to explore the influence of geometric and material parameters on the load-carrying capacity of elliptical CFST short columns. Furthermore, the current study investigates the effectiveness of machine learning (ML) techniques in predicting the load-carrying capacity of elliptical CFST short columns. These techniques include Support Vector Regressor (SVR), Ran

SUBMITTER: Mohamed HS 

PROVIDER: S-EPMC11541875 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature