TY - JOUR
T1 - New prediction model for the ultimate axial capacity of concrete-filled steel tubes
T2 - An evolutionary approach
AU - Javed, Muhammad Faisal
AU - Farooq, Furqan
AU - Memon, Shazim Ali
AU - Akbar, Arslan
AU - Khan, Mohsin Ali
AU - Aslam, Fahid
AU - Alyousef, Rayed
AU - Alabduljabbar, Hisham
AU - Ur Rehman, Sardar Kashif
N1 - Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2020/9
Y1 - 2020/9
N2 - The complication linked with the prediction of the ultimate capacity of concrete-filled steel tubes (CFST) short circular columns reveals a need for conducting an in-depth structural behavioral analyses of this member subjected to axial-load only. The distinguishing feature of gene expression programming (GEP) has been utilized for establishing a prediction model for the axial behavior of long CFST. The proposed equation correlates the ultimate axial capacity of long circular CFST with depth, thickness, yield strength of steel, the compressive strength of concrete and the length of the CFST, without need for conducting any expensive and laborious experiments. A comprehensive CFST short circular column under an axial load was obtained from extensive literature to build the proposed models, and subsequently implemented for verification purposes. This model consists of extensive database literature and is comprised of 227 data samples. External validations were carried out using several statistical criteria recommended by researchers. The developed GEP model demonstrated superior performance to the available design methods for AS5100.6, EC4, AISC, BS, DBJ and AIJ design codes. The proposed design equations can be reliably used for pre-design purposes—or may be used as a fast check for deterministic solutions.
AB - The complication linked with the prediction of the ultimate capacity of concrete-filled steel tubes (CFST) short circular columns reveals a need for conducting an in-depth structural behavioral analyses of this member subjected to axial-load only. The distinguishing feature of gene expression programming (GEP) has been utilized for establishing a prediction model for the axial behavior of long CFST. The proposed equation correlates the ultimate axial capacity of long circular CFST with depth, thickness, yield strength of steel, the compressive strength of concrete and the length of the CFST, without need for conducting any expensive and laborious experiments. A comprehensive CFST short circular column under an axial load was obtained from extensive literature to build the proposed models, and subsequently implemented for verification purposes. This model consists of extensive database literature and is comprised of 227 data samples. External validations were carried out using several statistical criteria recommended by researchers. The developed GEP model demonstrated superior performance to the available design methods for AS5100.6, EC4, AISC, BS, DBJ and AIJ design codes. The proposed design equations can be reliably used for pre-design purposes—or may be used as a fast check for deterministic solutions.
KW - Axial capacity
KW - Concrete-filled steel tube (CFST)
KW - Euler’s buckling load
KW - GEP-based model
KW - Genetic engineering programming (GEP)
UR - https://www.scopus.com/pages/publications/85090539940
U2 - 10.3390/cryst10090741
DO - 10.3390/cryst10090741
M3 - Article
AN - SCOPUS:85090539940
SN - 2073-4352
VL - 10
SP - 1
EP - 33
JO - Crystals
JF - Crystals
IS - 9
M1 - 741
ER -