Simulating buoyancy-driven airflow in buildings by coarse-grid fast fluid dynamics
| Autor: | Qingyan Chen, Wei Liu, Mingang Jin |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Environmental Engineering
Buoyancy business.industry Computer science Geography Planning and Development Displacement ventilation Airflow Stratification (water) Mechanical engineering Natural ventilation Building and Construction Mechanics Computational fluid dynamics engineering.material Plume Physics::Fluid Dynamics Fluid dynamics engineering business Civil and Structural Engineering |
| Zdroj: | Building and Environment. 85:144-152 |
| ISSN: | 0360-1323 |
| DOI: | 10.1016/j.buildenv.2014.11.028 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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