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

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.

Authors:
 [1];  [2];  [1];  [1];  [3];  [1]
  1. Southeast Univ., Nanjing (China)
  2. China Overseas Property, Zhengzhou (China)
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC); National Natural Science Foundation of China (NSFC); USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1581071
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Sustainability (Basel)
Additional Journal Information:
Journal Name: Sustainability (Basel); Journal Volume: 11; Journal Issue: 13; Journal ID: ISSN 2071-1050
Publisher:
MDPI
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; dry and hot areas; outdoor thermal comfort; urban morphology; urban performance simulation; genetic algorithm-driven

Citation Formats

Xu, Xiaodong, Yin, Chenhuan, Wang, Wei, Xu, Ning, Hong, Tianzhen, and Li, Qi. Revealing Urban Morphology and Outdoor Comfort through Genetic Algorithm-Driven Urban Block Design in Dry and Hot Regions of China. United States: N. p., 2019. Web. doi:10.3390/su11133683.
Xu, Xiaodong, Yin, Chenhuan, Wang, Wei, Xu, Ning, Hong, Tianzhen, & Li, Qi. Revealing Urban Morphology and Outdoor Comfort through Genetic Algorithm-Driven Urban Block Design in Dry and Hot Regions of China. United States. https://doi.org/10.3390/su11133683
Xu, Xiaodong, Yin, Chenhuan, Wang, Wei, Xu, Ning, Hong, Tianzhen, and Li, Qi. Thu . "Revealing Urban Morphology and Outdoor Comfort through Genetic Algorithm-Driven Urban Block Design in Dry and Hot Regions of China". United States. https://doi.org/10.3390/su11133683. https://www.osti.gov/servlets/purl/1581071.
@article{osti_1581071,
title = {Revealing Urban Morphology and Outdoor Comfort through Genetic Algorithm-Driven Urban Block Design in Dry and Hot Regions of China},
author = {Xu, Xiaodong and Yin, Chenhuan and Wang, Wei and Xu, Ning and Hong, Tianzhen and Li, Qi},
abstractNote = {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.},
doi = {10.3390/su11133683},
journal = {Sustainability (Basel)},
number = 13,
volume = 11,
place = {United States},
year = {2019},
month = {7}
}

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