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Large-Eddy Simulations of Wind-Driven Cross Ventilation, Part1: Validation and Sensitivity Study

Autor(en):

Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Frontiers in Built Environment, , v. 8
DOI: 10.3389/fbuil.2022.911005
Abstrakt:

Natural ventilation is gaining popularity in response to an increasing demand for a sustainable and healthy built environment, but the design of a naturally ventilated building can be challenging due to the inherent variability in the operating conditions that determine the natural ventilation flow. Large-eddy simulations (LES) have significant potential as an analysis method for natural ventilation flow, since they can provide an accurate prediction of turbulent flow at any location in the computational domain. However, the simulations can be computationally expensive, and few validation and sensitivity studies with respect to simulation parameters such as grid resolution and boundary conditions have been reported. The objectives of this study are to validate LES of wind-driven cross-ventilation and to quantify the sensitivity of the solution to the grid resolution and the inflow boundary conditions. We perform LES for an isolated building with two openings, using three different grid resolutions and two different inflow conditions with varying turbulence intensities. Predictions of the ventilation rate are compared to a reference wind-tunnel experiment available from literature, and we also quantify the age of air and ventilation efficiency. For the cross-ventilation case modeled in this paper, the prediction of the mean ventilation flow rate is very robust, showing negligible sensitivity to the grid resolution or the inflow characteristics with the maximum error of 1.9 and 1.3% for each sensitivity study. However, a sufficiently fine grid resolution is required to obtain accurate predictions of the detailed flow pattern and the age of air as they show comparably larger errors of 10 and 20% in the grid sensitivity study, and the standard deviation of the instantaneous ventilation rate is affected by the turbulence in the inflow condition with showing 44% difference.

Copyright: © 2022 Yunjae Hwang, Catherine Gorlé
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
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  • Reference-ID
    10690308
  • Veröffentlicht am:
    13.08.2022
  • Geändert am:
    10.11.2022
 
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