Multi-objective aerodynamic optimization of the exterior shape of tall buildings with trilateral cross-section
Wind-induced loads are largely dependent upon the exterior shape of buildings, and one highly effective procedure to mitigate them is to apply aerodynamic shape modifications in the aerodynamic optimization procedure (AOP). This study presents the framework of an AOP for shape modifications of the t...
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| Format: | Article |
| Language: | English |
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Semnan University
2022-11-01
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| Series: | Journal of Rehabilitation in Civil Engineering |
| Subjects: | |
| Online Access: | https://civiljournal.semnan.ac.ir/article_5970_0f56fcb1192bde69f1b3f2e248f7f411.pdf |
| _version_ | 1818028310318284800 |
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| author | Mehdi Noormohamadian Eysa Salajegheh |
| author_facet | Mehdi Noormohamadian Eysa Salajegheh |
| author_sort | Mehdi Noormohamadian |
| collection | DOAJ |
| description | Wind-induced loads are largely dependent upon the exterior shape of buildings, and one highly effective procedure to mitigate them is to apply aerodynamic shape modifications in the aerodynamic optimization procedure (AOP). This study presents the framework of an AOP for shape modifications of the trilateral cross-section tall buildings. The AOP is comprised of a combination of multi-objective optimization algorithm named non-dominated sorting genetic algorithm II (NSGA-II), artificial neural networks, and computational fluid dynamics. The building shape is designed based on the geometric description of its vertical and horizontal profile using seven geometric parameters (design variables) to apply different types and sizes of modifications. In addition, the mean moment coefficients in drag and lift directions are considered as the objective functions. The proposed procedure investigates the effect of the three types of modifications including varying cross-section sizes along the height, twisting, and curved-side on the reduction of objective functions. Finally, a set of optimal building shapes is presented as the Pareto front solutions, which enables the designers to select the optimal shape of the building with additional considerations. The results indicate the high capability of the proposed framework to make appropriate use of various aerodynamic modifications in order to upgrade the aerodynamic performance of the trilateral cross-section tall buildings. |
| first_indexed | 2024-12-10T05:01:46Z |
| format | Article |
| id | doaj.art-69e41e2c96dd40dbb11e174ee065111b |
| institution | Directory Open Access Journal |
| issn | 2345-4415 2345-4423 |
| language | English |
| last_indexed | 2024-12-10T05:01:46Z |
| publishDate | 2022-11-01 |
| publisher | Semnan University |
| record_format | Article |
| series | Journal of Rehabilitation in Civil Engineering |
| spelling | doaj.art-69e41e2c96dd40dbb11e174ee065111b2022-12-22T02:01:21ZengSemnan UniversityJournal of Rehabilitation in Civil Engineering2345-44152345-44232022-11-0110412914510.22075/jrce.2021.23611.15155970Multi-objective aerodynamic optimization of the exterior shape of tall buildings with trilateral cross-sectionMehdi Noormohamadian0Eysa Salajegheh1Department of Civil Engineering, Shahid Bahonar University of Kerman, IranDepartment of Civil Engineering, Shahid Bahonar University of Kerman, IranWind-induced loads are largely dependent upon the exterior shape of buildings, and one highly effective procedure to mitigate them is to apply aerodynamic shape modifications in the aerodynamic optimization procedure (AOP). This study presents the framework of an AOP for shape modifications of the trilateral cross-section tall buildings. The AOP is comprised of a combination of multi-objective optimization algorithm named non-dominated sorting genetic algorithm II (NSGA-II), artificial neural networks, and computational fluid dynamics. The building shape is designed based on the geometric description of its vertical and horizontal profile using seven geometric parameters (design variables) to apply different types and sizes of modifications. In addition, the mean moment coefficients in drag and lift directions are considered as the objective functions. The proposed procedure investigates the effect of the three types of modifications including varying cross-section sizes along the height, twisting, and curved-side on the reduction of objective functions. Finally, a set of optimal building shapes is presented as the Pareto front solutions, which enables the designers to select the optimal shape of the building with additional considerations. The results indicate the high capability of the proposed framework to make appropriate use of various aerodynamic modifications in order to upgrade the aerodynamic performance of the trilateral cross-section tall buildings.https://civiljournal.semnan.ac.ir/article_5970_0f56fcb1192bde69f1b3f2e248f7f411.pdfwind loadtall buildingcomputational fluid dynamicsmulti-objective optimizationartificial neural networks |
| spellingShingle | Mehdi Noormohamadian Eysa Salajegheh Multi-objective aerodynamic optimization of the exterior shape of tall buildings with trilateral cross-section Journal of Rehabilitation in Civil Engineering wind load tall building computational fluid dynamics multi-objective optimization artificial neural networks |
| title | Multi-objective aerodynamic optimization of the exterior shape of tall buildings with trilateral cross-section |
| title_full | Multi-objective aerodynamic optimization of the exterior shape of tall buildings with trilateral cross-section |
| title_fullStr | Multi-objective aerodynamic optimization of the exterior shape of tall buildings with trilateral cross-section |
| title_full_unstemmed | Multi-objective aerodynamic optimization of the exterior shape of tall buildings with trilateral cross-section |
| title_short | Multi-objective aerodynamic optimization of the exterior shape of tall buildings with trilateral cross-section |
| title_sort | multi objective aerodynamic optimization of the exterior shape of tall buildings with trilateral cross section |
| topic | wind load tall building computational fluid dynamics multi-objective optimization artificial neural networks |
| url | https://civiljournal.semnan.ac.ir/article_5970_0f56fcb1192bde69f1b3f2e248f7f411.pdf |
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