2001
DOI: 10.1016/s0167-6105(01)00106-4
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Study of natural ventilation in buildings by large eddy simulation

Abstract: Natural ventilation in buildings can create a comfortable and healthy indoor environment, and can save energy used in the mechanical ventilation systems. Two subgrid-scale models of large eddy simulation (LES), a Smagorinsky subgrid-scale (SS) model and a Filtered dynamic subgrid-scale (FDS) model, have been used to study airflow in buildings with natural ventilation. It was found that, for fully developed turbulence flow with a high Reynolds number, both the SS and FDS models provide good results. However, if… Show more

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Cited by 144 publications
(85 citation statements)
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“…Table 1 summarizes the performance of the three CFD methods in terms of computing time, available airflow information, and accuracy. The results for ventilation rate are the conclusions obtained from Jiang and Chen (2001). In that study, we also reported that FDS subgrid model used in LES is better than the SS model.…”
Section: Figure 2 the Locations Where Comparison Of The Cfd Results supporting
confidence: 80%
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“…Table 1 summarizes the performance of the three CFD methods in terms of computing time, available airflow information, and accuracy. The results for ventilation rate are the conclusions obtained from Jiang and Chen (2001). In that study, we also reported that FDS subgrid model used in LES is better than the SS model.…”
Section: Figure 2 the Locations Where Comparison Of The Cfd Results supporting
confidence: 80%
“…Table 2 also shows no significant difference between the mean ventilation rate and the average instantaneous ventilation rate. This is different from single-sided, wind-driven ventilation, where the average instantaneous ventilation rate is much higher than the mean value, since the fluctuating flow field plays a more important role there (Jiang and Chen 2001). On the other hand, the mean pressure difference across the opening in the singlesided, buoyancy-driven natural ventilation case is about ten times larger than the fluctuating pressure .…”
Section: Buoyancy-driven Natural Ventilationmentioning
confidence: 70%
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“…LES requires a larger time step than DNS; however, the computational cost with LES in terms of the memory and CPU time is larger than for the RANS models. LES was applied to predict the airflow distribution in an enclosed environment, as in the following studies (Davidson and Nielsen, 1996;Emmerich and McGrattan, 1998;Jiang and Chen, 2001;Musser and McGrattan, 2002). General detail on LES can be seen in Sagaut (2002).…”
Section: Computational Approachesmentioning
confidence: 99%
“…This results in lower ventilation rates and air change effectiveness (47). As the inlet air is at a greater velocity, the error will be increased compared to the lower inlet air velocities.…”
Section: Air Supply Ratesmentioning
confidence: 99%