Computational Approach to Predict Thermal Comfort Levels at Summer Peak Conditions in Passive House Based on Natural Ventilation

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Abstract

The Passive House building concept has been widely researched concerning its performance, especially aspects like energy consumption and thermal properties. Nevertheless, the design stages still do not present a dynamic thermal comfort predictive process that aids in investigating the design performance. This study focuses on a methodology that calculates summer months peak conditions in a pilot Passive House dwelling in the United Kingdom, based on the natural ventilation plan’s effectiveness in maintaining sufficient airflows. The methodology involves EnergyPlus dynamic simulations, ANSYS computational fluid dynamics simulations, and the Centre for the Built Environment Thermal Comfort Tool. The results showed a spectrum of predicted percentages of people dissatisfied ranging between 13.3−99.2% for different airspeeds, where the majority were of uncomfortable levels. Results also present ranges of thermal comfort parameters individually. The findings may add a comprehensive description to the thermal comfort status during design stages by employing the integrated software combination.

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Alhindawi, I., & Jimenez-Bescos, C. (2022). Computational Approach to Predict Thermal Comfort Levels at Summer Peak Conditions in Passive House Based on Natural Ventilation. Journal of Sustainable Development of Energy, Water and Environment Systems, 10(4). https://doi.org/10.13044/j.sdewes.d10.0419

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