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Simulating buoyancy-driven airflow in buildings by coarse-grid fast fluid dynamics
Abstract Fast fluid dynamics (FFD) is an intermediate model between multi-zone models and computational fluid dynamics (CFD) models for indoor airflow simulations. The use of coarse grids is preferred with FFD in order to increase computing speed. However, by using a very large mesh cell to represent a heat source that could have a much smaller physical size than the cell, coarse-grid FFD would under-predict the thermal plume and thermal stratification. This investigation integrated a thermal plume model into coarse-grid FFD. The integration first used the plume model to calculate a source for the momentum equations and then corrected the temperature at the plume cell. The integration enabled coarse-grid FFD to correctly predict the plumes. When applied to displacement ventilation, coarse-grid FFD with the plume model can accurately predict the mean air temperature stratification in rooms as compared with experimental data from the literature. The improved model has also been used to calculate the ventilation rate for buoyancy-driven natural ventilation. The calculated ventilation rates agree well with the experimental data or predictions by CFD and analytical models. Coarse-grid FFD with the plume model used only a small fraction of the computing time required by fine-grid FFD, while the associated errors for the two grid sizes were comparable.
Highlights This study integrated a thermal plume model into coarse-grid FFD. The integrated model was tested with buoyancy-driven airflow in buildings. The plume model can improve representing the heat source with very coarse cell. The integrated model used less computing time but maintained reasonable accuracy.
Simulating buoyancy-driven airflow in buildings by coarse-grid fast fluid dynamics
Abstract Fast fluid dynamics (FFD) is an intermediate model between multi-zone models and computational fluid dynamics (CFD) models for indoor airflow simulations. The use of coarse grids is preferred with FFD in order to increase computing speed. However, by using a very large mesh cell to represent a heat source that could have a much smaller physical size than the cell, coarse-grid FFD would under-predict the thermal plume and thermal stratification. This investigation integrated a thermal plume model into coarse-grid FFD. The integration first used the plume model to calculate a source for the momentum equations and then corrected the temperature at the plume cell. The integration enabled coarse-grid FFD to correctly predict the plumes. When applied to displacement ventilation, coarse-grid FFD with the plume model can accurately predict the mean air temperature stratification in rooms as compared with experimental data from the literature. The improved model has also been used to calculate the ventilation rate for buoyancy-driven natural ventilation. The calculated ventilation rates agree well with the experimental data or predictions by CFD and analytical models. Coarse-grid FFD with the plume model used only a small fraction of the computing time required by fine-grid FFD, while the associated errors for the two grid sizes were comparable.
Highlights This study integrated a thermal plume model into coarse-grid FFD. The integrated model was tested with buoyancy-driven airflow in buildings. The plume model can improve representing the heat source with very coarse cell. The integrated model used less computing time but maintained reasonable accuracy.
Simulating buoyancy-driven airflow in buildings by coarse-grid fast fluid dynamics
Jin, Mingang (author) / Liu, Wei (author) / Chen, Qingyan (author)
Building and Environment ; 85 ; 144-152
2014-11-13
9 pages
Article (Journal)
Electronic Resource
English
Simulating buoyancy-driven airflow in buildings by coarse-grid fast fluid dynamics
Online Contents | 2015
|Simulating buoyancy-driven airflow in buildings by coarse-grid fast fluid dynamics
British Library Online Contents | 2015
|Simulating buoyancy-driven airflow in buildings by coarse-grid fast fluid dynamics
British Library Online Contents | 2015
|Taylor & Francis Verlag | 2018
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