Modeling of coupled urban wind flow and indoor air flow on a high-density near-wall mesh: Sensitivity analyses and case study for single-sided ventilation

Coupled urban wind flow and indoor air flow is an important flow problem that is associated with many environmental processes. This paper provides detailed sensitivity analyses of some important computational parameters that may influence the prediction accuracy of such a flow problem. The CFD predi...

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Veröffentlicht in:Environmental modelling & software : with environment data news 2014-10, Vol.60, p.57-68
Hauptverfasser: Ai, Z.T., Mak, C.M.
Format: Artikel
Sprache:eng
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Zusammenfassung:Coupled urban wind flow and indoor air flow is an important flow problem that is associated with many environmental processes. This paper provides detailed sensitivity analyses of some important computational parameters that may influence the prediction accuracy of such a flow problem. The CFD prediction of single-sided ventilation rate is taken as a case study. Based on both the RANS and LES turbulence models, the most commonly used predictive methods, namely the integration and tracer gas decay methods, are examined. A range of wind directions are considered, since the characteristics of both building aerodynamics and ventilation mechanics are distinctive under different wind directions. The performance of numerical model is thoroughly evaluated, including validation against field measurements. Specific attention is paid to sensitivity analyses of the near-wall mesh density. The implications for accurate CFD prediction of the single-sided ventilation rate are summarized, which are also applicable to other coupled flows. •Performance of RANS model is analyzed in comparison with LES model.•Near-wall mesh independence is tested for both mathematical models.•Integration and tracer gas decay methods are compared based on their mechanisms.•Variation of the single-sided ventilation rate with wind direction is studied.•Implications for future CFD prediction of coupled urban and indoor flow are provided.
ISSN:1364-8152
1873-6726
DOI:10.1016/j.envsoft.2014.06.010