Open Access
Thermal Environmental Conditions for Human Occupancy
Standard Ashrae
- Vol. 5
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The article was published on 1992-01-01 and is currently open access. It has received 5855 citations till now. The article focuses on the topics: Occupancy.read more
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Do biometeorological indices improve modeling outcomes of heat-related mortality?
TL;DR: In this article, the authors compared the performance of several common biometeorological indices and temperature measures in evaluating the heat-related mortality in Brisbane, Australia, a city with a subtropical climate.
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Physiological modeling for technical, clinical and research applications.
Dusan Fiala,Agnes Psikuta,Gerd Jendritzky,Stefan Paulke,David A. Nelson,Wouter D. van Marken Lichtenbelt,Arjan J. H. Frijns +6 more
TL;DR: A dynamic simulation model is presented and used to predict human thermophysiological and perceptual responses for different applications and situations and predicts body temperatures, thermoregulatory responses, and components of the environmental heat exchange in cold, moderate, as well as hot stress conditions.
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Human Response to an Individually Controlled Microenvironment
TL;DR: In this article, an individually controlled system (ICS) comprising personalized ventilation, an under-desk air terminal device supplying cool air, a chair with convectively heated backrest, and an underdesk radiant heating panel, and a floor heating panel was used.
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Field study of mixed-mode office buildings in Southern Brazil using an adaptive thermal comfort framework
TL;DR: In this paper, the authors conducted field studies on thermal comfort in three mixed-mode office buildings in the city of Florianopolis (a temperate and humid climate), Southern Brazil, and found that occupants adapted to indoor temperature fluctuations as predicted by the adaptive thermal comfort theory.
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Thermal comfort control using a non-linear MPC strategy: A real case of study in a bioclimatic building
TL;DR: In this article, a hierarchical thermal comfort control system with two layers is presented, the upper layer includes a non-linear model predictive controller that allows to obtain a high thermal comfort level by optimizing the use of an HVAC system in order to reduce, as much as possible, the energy consumption.