Issue |
E3S Web Conf.
Volume 111, 2019
CLIMA 2019 Congress
|
|
---|---|---|
Article Number | 04049 | |
Number of page(s) | 6 | |
Section | High Energy Performance and Sustainable Buildings, Simulation models and predictive tools for the buildings HVAC, IEQ and energy | |
DOI | https://doi.org/10.1051/e3sconf/201911104049 | |
Published online | 13 August 2019 |
Dynamic design model of displacement ventilation
1 Aalto University, Department of mechanical engineering, Sähkömiehentie 4, 00076, Espoo, Finland
2 College of Urban Construction, Nanjing Tech University, China
* Corresponding author: natalia.lastovets@aalto.fi
An accurate temperature gradient calculation is essential for displacement ventilation (DV) system design, since it directly relates to the calculation of the required supply air flow rate. Inaccurate temperature prediction can cause the poor thermal comfort and w sizing of the ventilation and cooling systems. Several simplified nodal models were developed and implemented in the various building simulation software to estimate the temperature stratification in rooms with DV. Recent studies reveal that the multi-nodal models provide the most accurate temperature gradient prediction. However, the most building simulation software uses the air models with only one air node. The present study introduces the dynamic temperature gradient model for DV and investigates the effect of thermal mass on the temperature stratification. The model was validated with the experimental results of the lecture room with displacement ventilation. The room air temperature measurements were conducted during three weeks at 20 different heights. The supply air temperature and occupancy rate were recorded during each scheduled lecture. The developed dynamic nodal model is able to accurately calculate the air temperatures in occupied zone. The effect of the thermal mass and varied heat loads on the indoor air temperature stratification is analysed for the lecture room with DV.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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