New Prediction Model for the Ultimate Axial Capacity of Concrete-Filled Steel Tubes: An Evolutionary Approach

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@Article{javed:2020:Crystals,

• author = "Muhammad Faisal Javed and Furqan Farooq and Shazim Ali Memon and Arslan Akbar and Mohsin Ali Khan and Fahid Aslam and Rayed Alyousef and Hisham Alabduljabbar and Sardar Kashif Ur Rehman",
• title = "New Prediction Model for the Ultimate Axial Capacity of {Concrete-Filled} Steel Tubes: An Evolutionary Approach",
• journal = "Crystals",
• year = "2020",
• volume = "10",
• number = "9",
• keywords = "genetic algorithms, genetic programming, gene expression programming",
• ISSN = "2073-4352",
• URL = "https://www.mdpi.com/2073-4352/10/9/741",
• DOI = "doi:10.3390/cryst10090741",
• abstract = "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 behavioural analyses of this member subjected to axial-load only. The distinguishing feature of gene expression programming (GEP) has been used for establishing a prediction model for the axial behaviour 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.",
• notes = "also known as \cite{cryst10090741}",

}

Genetic Programming entries for Muhammad Faisal Javed Furqan Farooq Shazim Ali Memon Arslan Akbar Mohsin Ali Khan Fahid Aslam Rayed Alyousef Hisham Alabduljabbar Sardar Kashif Ur Rehman

Citations