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Revealing Urban Morphology and Outdoor Comfort through Genetic Algorithm-Driven Urban Block Design in Dry and Hot Regions of China

1
School of Architecture, Southeast University, Nanjing 210018, China
2
China Overseas Property, Zhengzhou 450000, China
3
Lawrence Berkeley National Laboratory, Building Technology and Urban Systems Division, Berkeley, CA 94720, USA
*
Authors to whom correspondence should be addressed.
Sustainability 2019, 11(13), 3683; https://doi.org/10.3390/su11133683
Received: 16 June 2019 / Revised: 2 July 2019 / Accepted: 2 July 2019 / Published: 4 July 2019
(This article belongs to the Collection Sustainable Built Environment)
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Abstract

In areas with a dry and hot climate, factors such as strong solar radiation, high temperature, low humidity, dazzling light, and dust storms can tremendously reduce people’s thermal comfort. Therefore, researchers are paying more attention to outdoor thermal comfort in urban environments as part of urban design. This study proposed an automatic workflow to optimize urban spatial forms with the aim of improvement of outdoor thermal comfort conditions, characterized by the universal thermal climate index (UTCI). A city with a dry and hot climate—Kashgar, China—is further selected as an actual case study of an urban block and Rhino & Grasshopper is the platform used to conduct simulation and optimization process with the genetic algorithm. Results showed that in summer, the proposed method can reduce the averaged UTCI from 31.17 to 27.43 °C, a decrease of about 3.74 °C, and reduce mean radiation temperature (MRT) from 43.94 to 41.29 °C, a decrease of about 2.65 °C. View Full-Text
Keywords: dry and hot areas; outdoor thermal comfort; urban morphology; urban performance simulation; genetic algorithm-driven dry and hot areas; outdoor thermal comfort; urban morphology; urban performance simulation; genetic algorithm-driven
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Xu, X.; Yin, C.; Wang, W.; Xu, N.; Hong, T.; Li, Q. Revealing Urban Morphology and Outdoor Comfort through Genetic Algorithm-Driven Urban Block Design in Dry and Hot Regions of China. Sustainability 2019, 11, 3683.

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