Phan, DT, Lim, JBP, Sha, W, Siew, CYM, Tanyimboh, TT, Issa, HK and Mohammad, FA ORCID: https://orcid.org/0000-0001-6955-4261, 2013. Design optimization of cold-formed steel portal frames taking into account the effect of building topology. Engineering Optimization, 45 (4), pp. 415-433. ISSN 0305-215X
Preview |
Text
4428_Mohammadb.pdf - Post-print Download (525kB) | Preview |
Abstract
Cold-formed steel portal frames are a popular form of construction for low-rise commercial, light industrial and agricultural buildings with spans of up to 20 m. In this article, a real-coded genetic algorithm is described that is used to minimize the cost of the main frame of such buildings. The key decision variables considered in this proposed algorithm consist of both the spacing and pitch of the frame as continuous variables, as well as the discrete section sizes. A routine taking the structural analysis and frame design for cold-formed steel sections is embedded into a genetic algorithm. The results show that the real-coded genetic algorithm handles effectively the mixture of design variables, with high robustness and consistency in achieving the optimum solution. All wind load combinations according to Australian code are considered in this research. Results for frames with knee braces are also included, for which the optimization achieved even larger savings in cost.
Item Type: | Journal article |
---|---|
Publication Title: | Engineering Optimization |
Creators: | Phan, D.T., Lim, J.B.P., Sha, W., Siew, C.Y.M., Tanyimboh, T.T., Issa, H.K. and Mohammad, F.A. |
Publisher: | Taylor & Francis |
Date: | 2013 |
Volume: | 45 |
Number: | 4 |
ISSN: | 0305-215X |
Identifiers: | Number Type 10.1080/0305215X.2012.678493 DOI |
Divisions: | Schools > School of Architecture, Design and the Built Environment |
Record created by: | Jonathan Gallacher |
Date Added: | 25 Feb 2016 10:59 |
Last Modified: | 09 Jun 2017 13:59 |
URI: | https://irep.ntu.ac.uk/id/eprint/27038 |
Actions (login required)
Edit View |
Statistics
Views
Views per month over past year
Downloads
Downloads per month over past year