A machine learning based interaction model to predict robustness of concrete-filled double skin steel tubular columns under fire condition
Author:
Publisher
Elsevier BV
Subject
Safety, Risk, Reliability and Quality,Building and Construction,Architecture,Civil and Structural Engineering
Reference38 articles.
1. Behaviour of slender concrete-filled dual steel tubular columns subjected to eccentric loads;Albero;J Constr Steel Res,2021
2. Numerical modeling of axially loaded circular concrete-filled double-skin steel tubular short columns incorporating a new concrete confinement model;Ahmed;Structures,2021
3. Effect of steel and concrete thickness on shear strength of square concrete filled double skin tubular beams;Ullah;Case Stud Constr Mater,2021
4. Computational simulation of eccentrically loaded circular thin-walled concrete-filled double steel tubular slender columns;Ahmed;Eng Struct,2020
5. Fire performance of self-consolidating concrete filled double skin steel tubular columns: Experiments;Lu;Fire Saf J,2010
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1. Machine learning-based prediction of concrete strength properties with coconut shell as partial aggregate replacement: A sustainable approach in construction engineering;Asian Journal of Civil Engineering;2023-12-29
2. Enhancing load capacity prediction of column using eReLU-activated BPNN model;Structures;2023-12
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