4.7 Article

Development of the ASHRAE Global Thermal Comfort Database II

期刊

BUILDING AND ENVIRONMENT
卷 142, 期 -, 页码 502-512

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.buildenv.2018.06.022

关键词

Thermal comfort; Field study; Data repository; Visualization tool

资金

  1. American Society of Heating, Refrigerating and Air-Conditioning Engineers grant [URP 1656]
  2. 2017 ASHRAE Graduate Grant-In-Aid for Veronika Foldvary Lana
  3. British Council and UK Government under the Global Innovation Initiative project scheme
  4. Korea National Science Foundation
  5. Center for the Built Environment, University of California Berkeley
  6. Republic of Singapore's National Research Foundation

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Recognizing the value of open-source research databases in advancing the art and science of HVAC, in 2014 the ASHRAE Global Thermal Comfort Database II project was launched under the leadership of University of California at Berkeley's Center for the Built Environment and The University of Sydney's Indoor Environmental Quality (IEQ) Laboratory. The exercise began with a systematic collection and harmonization of raw data from the last two decades of thermal comfort field studies around the world. The ASHRAE Global Thermal Comfort Database II (Comfort Database), now an online, open-source database, includes approximately 81,846 complete sets of objective indoor climatic observations with accompanying right-here-right-now subjective evaluations by the building occupants who were exposed to them. The database is intended to support diverse inquiries about thermal comfort in field settings. A simple web-based interface to the database enables filtering on multiple criteria, including building typology, occupancy type, subjects' demographic variables, subjective thermal comfort states, indoor thermal environmental criteria, calculated comfort indices, environmental control criteria and outdoor meteorological information. Furthermore, a web-based interactive thermal comfort visualization tool has been developed that allows end-users to quickly and interactively explore the data.

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