席天宇
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教授
博士生导师
硕士生导师
- 教师拼音名称：xitianyu
- 入职时间：2020-09-21
- 所在单位：江河建筑学院
- 职务：教授（长聘）
- 学历：博士研究生毕业
- 性别：男
- 联系方式：5cca5cecef4bc9212691eb46aaeb9f229039d0de93ca27f177c8133099edd9786c75c1489188ccc3c94cb96a64107aefb949ebb94985cfd58612ecb42bd7672e978cb9eb251c3c706316ba499ecce765a7daa7da380bfab58aa5ee8187ce1909f4835df49164eb89349bda376c342e61aa1e2d8b11a1dcf6d4038cfe87ceb77f
- 学位：博士
- 在职信息：在职
- 主要任职：副院长，教授，博导，沈阳市领军人才
- 毕业院校：日本东北大学（Tohoku University）
访问量：
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[1]Impacts of Cold Waves and Urban Heat Islands on Heating Energy Consumption Differences Across Intra-Local Climate Zones.buildings
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[2]Differential effects of long-term regional thermal adaptation on short-term outdoor thermal experiences: local people vs. tourists in a mild-humid winter climate.INTERNATIONAL JOURNAL OF BIOMETEOROLOGY
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[3]Thermal environment characteristics of local climate zones during winter cold waves in severe cold regions.Case Studies in Thermal Engineering
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[4]Thermal environment mechanism across intra local climate zones in summer in a northern city in China: A case study of Shenyang.Sustainable Cities and Society
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[5]Thermal Environment Characteristics of Local Climate Zones Based on Summer Stage Subdivision: An Observational Study in Shenyang, China.Land
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[6]Wang, Shanshan,Wang, Lan*,Wu, Haoru,Chen, Xiquan,Xu, Wenwen,席天宇.Impact of age on children's outdoor thermal sensation in a hot and humid climate.BUILDING AND ENVIRONMENT,271.10.1016/j.buildenv.2025.112652,
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[7]席天宇*,李瑾,Guo, Fei.Analysis of the Characteristics of Heat Island Intensity Based on Local Climate Zones in the Transitional Season of Shenyang.ENERGIES,18(5):.10.3390/en18051053,
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[8]席天宇*,Wang, Ming,Guo, Fei.Optimization of Residential Indoor Thermal Environment by Passive Design and Mechanical Ventilation in Tropical Savanna Climate Zone in Nigeria, Africa.ENERGIES,18(3):.10.3390/en18030450,
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[9]A preliminary study of multidimensional semantic evaluation of outdoor thermal comfort in Chinese.Architectural Intelligence
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[10]席天宇*,Wang, Yong.Preliminary Research on Outdoor Thermal Comfort Evaluation in Severe Cold Regions by Machine Learning.BUILDINGS,14(1):.10.3390/buildings14010284,
