Genetic Algorithm for Optimizing Urban District and Block Morphology to Minimize Solar Radiation Access and Maximize Building Floor Area in the UAE
Due to climate change, enhancing outdoor and indoor thermal comfort is increasingly important. Solar radiation drives temperature increases, making solar exposure reduction essential in urban design. Most previous research has focused on parametric analysis to optimize small urban blocks, often over...
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MDPI AG
2024-12-01
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| Online Access: | https://www.mdpi.com/2075-5309/14/12/3898 |
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| author | Hanan M. Taleb Mays Kayed Fuad Baba |
| author_facet | Hanan M. Taleb Mays Kayed Fuad Baba |
| author_sort | Hanan M. Taleb |
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| description | Due to climate change, enhancing outdoor and indoor thermal comfort is increasingly important. Solar radiation drives temperature increases, making solar exposure reduction essential in urban design. Most previous research has focused on parametric analysis to optimize small urban blocks, often overlooking the impact of the overall urban district (UD) on reducing Solar Radiation Access (SRA). This work aims to find the optimized UD to minimize SRA and maximize Floor Area (FA). The proposed methodology is developed to achieve these objective functions using a single-objective Genetic Algorithm (GA) with three street layout patterns: random, radial, and grid layout. Further SRA analysis is conducted at the urban block level, focusing on blocks with the highest SRA in the optimized UD to achieve further SRA reduction while maintaining the same FA. Dubai Silicon Oasis district in the UAE was selected as a case study. Elk2-0.3.1 (GIS data), Ladybug (1.7.0), DeCodingSpaces-Toolbox (2021.10), and Galapagos (1.0.0007) Plugins in Grasshopper (0.9.0076) were used. The results show that the radial street pattern achieved better results with an 8.4% reduction in SRA with an 8.9% increase in FA. Additional analysis of the blocks with the highest SRA can achieve an additional 7.4% reduction in SRA. |
| format | Article |
| id | doaj-art-a2ae58c63de846d589c7f75e8e2a864e |
| institution | DOAJ |
| issn | 2075-5309 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
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| series | Buildings |
| spelling | doaj-art-a2ae58c63de846d589c7f75e8e2a864e2025-08-20T02:57:12ZengMDPI AGBuildings2075-53092024-12-011412389810.3390/buildings14123898Genetic Algorithm for Optimizing Urban District and Block Morphology to Minimize Solar Radiation Access and Maximize Building Floor Area in the UAEHanan M. Taleb0Mays Kayed1Fuad Baba2Faculty of Engineering, British University in Dubai, Dubai 345015, United Arab EmiratesFaculty of Engineering, British University in Dubai, Dubai 345015, United Arab EmiratesFaculty of Engineering, British University in Dubai, Dubai 345015, United Arab EmiratesDue to climate change, enhancing outdoor and indoor thermal comfort is increasingly important. Solar radiation drives temperature increases, making solar exposure reduction essential in urban design. Most previous research has focused on parametric analysis to optimize small urban blocks, often overlooking the impact of the overall urban district (UD) on reducing Solar Radiation Access (SRA). This work aims to find the optimized UD to minimize SRA and maximize Floor Area (FA). The proposed methodology is developed to achieve these objective functions using a single-objective Genetic Algorithm (GA) with three street layout patterns: random, radial, and grid layout. Further SRA analysis is conducted at the urban block level, focusing on blocks with the highest SRA in the optimized UD to achieve further SRA reduction while maintaining the same FA. Dubai Silicon Oasis district in the UAE was selected as a case study. Elk2-0.3.1 (GIS data), Ladybug (1.7.0), DeCodingSpaces-Toolbox (2021.10), and Galapagos (1.0.0007) Plugins in Grasshopper (0.9.0076) were used. The results show that the radial street pattern achieved better results with an 8.4% reduction in SRA with an 8.9% increase in FA. Additional analysis of the blocks with the highest SRA can achieve an additional 7.4% reduction in SRA.https://www.mdpi.com/2075-5309/14/12/3898solar reflectance accessurban districtmorphologyurban blocksUAEgenetic algorithm |
| spellingShingle | Hanan M. Taleb Mays Kayed Fuad Baba Genetic Algorithm for Optimizing Urban District and Block Morphology to Minimize Solar Radiation Access and Maximize Building Floor Area in the UAE Buildings solar reflectance access urban district morphology urban blocks UAE genetic algorithm |
| title | Genetic Algorithm for Optimizing Urban District and Block Morphology to Minimize Solar Radiation Access and Maximize Building Floor Area in the UAE |
| title_full | Genetic Algorithm for Optimizing Urban District and Block Morphology to Minimize Solar Radiation Access and Maximize Building Floor Area in the UAE |
| title_fullStr | Genetic Algorithm for Optimizing Urban District and Block Morphology to Minimize Solar Radiation Access and Maximize Building Floor Area in the UAE |
| title_full_unstemmed | Genetic Algorithm for Optimizing Urban District and Block Morphology to Minimize Solar Radiation Access and Maximize Building Floor Area in the UAE |
| title_short | Genetic Algorithm for Optimizing Urban District and Block Morphology to Minimize Solar Radiation Access and Maximize Building Floor Area in the UAE |
| title_sort | genetic algorithm for optimizing urban district and block morphology to minimize solar radiation access and maximize building floor area in the uae |
| topic | solar reflectance access urban district morphology urban blocks UAE genetic algorithm |
| url | https://www.mdpi.com/2075-5309/14/12/3898 |
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