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Predicting thermal and energy performance of mixed-mode ventilation using an integrated simulation approach

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  • Indoor/Outdoor Airflow and Air Quality
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Abstract

Mixed-mode ventilation can effectively reduce energy consumption in buildings, as well as improve thermal comfort and productivity of occupants. This study predicts thermal and energy performance of mixed-mode ventilation by integrating computational fluid dynamics (CFD) with energy simulation. In the simulation of change-over mixed-mode ventilation, it is critical to determine whether outdoor conditions are suitable for natural ventilation at each time step. This study uses CFD simulations to search for the outdoor temperature thresholds when natural ventilation alone is adequate for thermal comfort. The temperature thresholds for wind-driven natural ventilation are identified by a heat balance model, in which air change rate (ACH) is explicitly computed by CFD considering the influence of the surrounding buildings. In buoyancy-driven natural ventilation, the outdoor temperature thresholds are obtained directly from CFD-based parametric analysis. The integrated approach takes advantage of both the CFD algorithm and energy simulation while maintaining low levels of complexity, enabling building designers to utilize this method for early-stage decisionmaking. This paper first describes the workflow of the proposed integrated approach, followed by two case studies, which are presented using a three-floor office building in an urban context. The results are compared with those using an energy simulation program with built-in multizone modules for natural ventilation. Additionally, adaptive thermal comfort models are applied in these case studies, which shows the possibility of further reducing the electricity used for cooling.

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Correspondence to Bin Yan.

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Malkawi, A., Yan, B., Chen, Y. et al. Predicting thermal and energy performance of mixed-mode ventilation using an integrated simulation approach. Build. Simul. 9, 335–346 (2016). https://doi.org/10.1007/s12273-016-0271-x

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  • DOI: https://doi.org/10.1007/s12273-016-0271-x

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