Evaluation of thermal environment by coupling CFD analysis and wireless-sensor measurements of a full-scale room with cooling system

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

64 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)395-405
Journal / PublicationSustainable Cities and Society
Volume45
Online published11 Dec 2018
Publication statusPublished - Feb 2019

Abstract

HVAC systems are utilized to construct a thermally comfortable environment for occupants. As people spend more than 90% of time indoors, thermal conditions of indoor environment constructed by HVAC systems demand precise assessment. Predicted mean vote (PMV), a synthesized index, can reveal thermal conditions by evaluating occupants’ thermal sensations. Four environmental parameters affecting PMV: air temperature, air speed, radiant temperature and relative humidity. This study integrates CFD simulations and wireless-sensor measurements to assess distributions of PMV considering radiation models. The distributions of environmental parameters: velocity, temperature, radiant temperature, inside an office room with fan coil unit (FCU) are firstly presented. Based on these distributions, spatial profiles of PMV are obtained to intuitively illustrate thermal conditions. Combined with experimental database collected by thermal-flow wireless-sensors, CFD simulations offer detailed predictions of indoor airflow and thermal parameters. The mean temperature at occupied zone is 23.3 °C agreeing well with set-point temperature 23 °C. Furthermore, velocity values are below draft sensation limitations. The distribution of PMV indicates the cooling system is capable to construct thermally comfortable environment for occupants as well as the draft sensation conforming the satisfactory status. The research outputs provide useful information for designers of cooling system to build a comfortable indoor environment.

Research Area(s)

  • CFD simulation, FCU cooling system, Radiation model, Thermal comfort, Wireless sensors