Comfort reliability evaluation of building designs by stochastic hygrothermal simulation

Outdoor climate jointly with architectonic design, housing materials, and construction system determine thermal performance of buildings and their ability to deliver comfortable conditions to occupants. Buildings must provide comfortable indoor environment which should be reasonably assured regardless of outdoor weather fluctuations. This paper presents a methodology for quantitatively measuring the hygrothermal discomfort risk of any building design. By combining a numeric model of the building hygrothermal response with stochastic simulation techniques, occurrence probability, expected frequency and duration of discomfort events in each thermal zone can be estimated. The article presents fundamental notions on probabilistic hygrothermal risk assessment, describes the developed numerical simulation models and introduces comfort reliability indexes. In order to illustrate the practicability of the proposed approach in the context of the design process, the methodology was applied to a prototype of a residential. house conventionally built and acclimatized. The materials and construction system reflect typical residential housing in the region of study. A bioclimatic variant of the same building design is also evaluated. Monte Carlo simulations of the building's thermal response under stochastic weather conditions allow identifying infrequent but critical situations in which the building is unable to meet comfort requirements. Statistical analysis of simulation results is performed and condensed in meaningful probabilistic indices for objectively measuring comfort reliability. By means of these metrics, shortcoming of the architectonic design can be revealed and properly amended. In addition, comfort reliability and risk indices facilitate the comparison of alternative thermal building designs on a fair basis. The proposed methodology and the developed models are general and they can be applied without constraints to any building design under a wide variety of climates. (C) 2014 Elsevier Ltd. All rights reserved.