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http://dx.doi.org/10.7734/COSEIK.2016.29.5.429

Genetic Algorithm Based Optimal Structural Design Method for Cost and CO2 Emissions of Reinforced Concrete Frames  

Lee, Min-Seok (Department of Architectural Engineering, Yonsei University)
Hong, Kappyo (Department of Architectural Engineering, Yonsei University)
Choi, Se-Woon (Department of Architecture, Catholic University of Daegu)
Publication Information
Journal of the Computational Structural Engineering Institute of Korea / v.29, no.5, 2016 , pp. 429-436 More about this Journal
Abstract
In this study, the genetic algorithm based optimal structural design method is proposed. The objective functions are to minimize the cost and $CO_2$ emissions, simultaneously. The cost and $CO_2$ emissions are calculated based on the cross-sectional dimensions, length, material strength, and reinforcement ratio of beam and column members. Thus, the cost and $CO_2$ emissions are evaluated by using the amounts of concrete and reinforcement used to construct a building. In this study, the cost and $CO_2$ emissions calculated at the phases of material transportation, construction, and building operation are excluded. The constraint conditions on the strength of beam and column members and the inter-story drift ratio are considered. The linear static analysis by using OpenSees is automatically conducted in the proposed method. The genetic algorithm is employed to solve the formulated problem. The proposed method is validated by applying it to the 4-story reinforced concrete moment frame example.
Keywords
cost; $CO_2$ emissions; reinforced concrete moment frame; genetic algorithm;
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Times Cited By KSCI : 3  (Citation Analysis)
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