The present research is conducted to investigate the behaviour of elliptical tube columns filled with self-compacting concrete (SCC). In total, ten specimens, including two empty columns, were tested to failure. The main parameters investigated were the length and the sections of the columns, and the concrete compressive strength. Artificial Neural Network (ANN) model was developed to predict the compressive strength of SCC using a comprehensive database collected from different previous studies. The database was used to train and test the developed ANN. Moreover, parallel to the experimental works, a three dimensional nonlinear finite element (FE) model using ABAQUS software was developed to predict the behaviour of SCC elliptical tube columns. The proposed ABAQUS model was verified against the current experimental results.
The experimental results indicated that the failure modes of the SCC filled elliptical steel tube columns having large slenderness ratios were dominated by global buckling. Moreover, the composite columns possessed higher critical axial compressive capacities compared with their hollow section companions due to the composite interaction. However, due to the large slenderness ratio of the test specimens, the change of compressive strength of concrete core did not show significant effect on the critical axial compressive capacity of concrete filled columns although the axial compressive capacity increased with the concrete grade increase. The comparisons between the axial compressive load capacities obtained from experimental study and those predicted using simple methods provided in Eurocode 4 for concrete-filled steel rectangular tube columns showed a reasonable agreement. The proposed three dimensional FE model accurately predicted the failure modes, the load capacity and the load-deflection response of the columns tested. The experimental results, analysis and comparisons presented in this thesis clearly support the application of self-compacting concrete filled elliptical steel tube columns in construction engineering practice.
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/14787 |
| Date | January 2016 |
| Creators | Mahgub, Munir |
| Contributors | Ashour, Ashraf, Lam, Dennis, Dai, Xianghe |
| Publisher | University of Bradford, Faculty of Engineering and Informatics |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Thesis, doctoral, PhD |
| Rights | <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>. |
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