No abstract

No abstract

No abstract

The present paper presents a full procedure to develop an adaptive comfort model for South-East Asia. Meta-analysis on large number of observations from field surveys which were conducted in this region was employed. Standardization and bias control of the database were fully reported. Statistical tests of significance and weighted regression method applied in the analyses strengthened the reliability of the findings. This paper found a great influence of 'Griffiths constant' on the establishment of adaptive comfort equation and proposed an appropriate value. The adaptive comfort model generated is applicable to naturally ventilated building under hot and humid conditions of South-East Asia. The mean neutral comfort temperature (operative temperature, effective temperature, standard effective temperature) in naturally ventilated and air-conditioned building was compared and the differences have been discussed. The similar neutral standard effective temperature in both naturally ventilated and air-conditioned building proposes a new idea to implement SET* into building simulation tools to assess thermal comfort without the attention of building classification.Through the analysis, the effectiveness of behavioral adaptive actions on occupant's thermal perception has been argued. The extended PMV-PPD model for hot humid conditions was examined and its applicability was recommended. Other comfort related issues, the differences and similarities between various adaptive comfort models were also addressed. Keywords: naturally ventilated building, meta-analysis, adaptive thermal comfort, South-EastAsia, hot humid climate IntroductionTaking into account thermal comfort is very important for architects and engineers to ensure comfort and health of occupant in the building. A good estimation of built environment not only offers comfortable thermal sensation to occupants, but it also determines the amount of energy that will be consumed by cooling and heating systems of the building. In the context of climate change and global warming, the inclusion of adaptive thermal comfort concept in the thermal comfort standards which allows adopting new energy efficiency strategies and consistently meeting the requirement of sustainable development makes it more relevant to present context.In the early 1970s, the 'steady state' thermal comfort theory proposed by Fanger [1] has become the foundation of international thermal comfort standards such as ISO 7730 [2] and ASHRAE 55 [3]. This model combines six conventional indexes (air temperature, mean radiant temperature, water vapor pressure, air velocity, occupant's clothing insulation and metabolic rate) to predict occupant's thermal sensation in a controlled climate chamber or air-conditioned (AC) environment. However, many field studies have shown that this model has failed to predict the thermal sensation of occupants living in "free running" buildings, not only in hot climates but also in temperate climates. The failure to predict the sensation happens because of the fact t...

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.