Ensemble Machine Learning Models for Estimating Mechanical Curves of Concrete-Timber-Filled Steel Tubes
Published: 16 June 2025| Version 2 | DOI: 10.17632/j7c3zwfvww.2
Contributors:
Farzin Kazemi, Neda Asgarkhani, Tohid Ghanbari-Ghazijahani, Robert JankowskiDescription
A set of 88 models of CTFSTs was provided in ABAQUS software, focusing on parameters of D, as steel tube diameter, D/t as the diameter-to-thickness ratio, and AT, AC, and AS for cross-sectional areas of timber, concrete, and steel, respectively. Moreover, fc, fy, and fT present the compressive strength of concrete, steel tube, and timber used in the CTFSTs. A full description of the inputs and outputs has been provided in the paper titled "Ensemble Machine Learning Models for Estimating Mechanical Curves of Concrete-Timber-Filled Steel Tubes" published in Engineering Applications of Artificial Intelligence. Please see the link below to find the paper.
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Institutions
- Politechnika Gdanska
- Macquarie University
Categories
Steel, Machine Learning, Machine Learning Algorithm, Machine Learning Theory, Graphical User Interface, Mechanical Property, Reinforced Concrete, Concrete Structure, Composite Structure, Concrete Filled Steel Tube, Composite Column, Timber, Automated Machine Learning