2005
DOI: 10.1080/14733315.2005.12021997
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Study on the Numerical Predictive Accuracy of Wind Pressure Distribution and Air Flow Characteristics—Part 1 Optimization of Turbulence Models for Practical Use; Part 2 Prediction Accuracy of Wind Pressure Distribution of Various Shaped Buildings

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Cited by 7 publications
(6 citation statements)
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“…To overcome this drawback, some authors have used revised k-ε models, such as the MMK model, the Durbin model, the Kato-Launder modification, the RNG k-ε model (Zhang and Gu, 2008), the realizable k-ε model (Montazeri and Blocken, 2013) or k-ω based models such as the SST model. Some authors have also made a model comparison (Kim and Patel, 2000;Endo et al, 2005;Guha et al, 2009;Tominaga and Stathopoulos, 2009;Ramponi and Blocken, 2012;Ai et al, 2013).…”
Section: Flow and Turbulence Modelingmentioning
confidence: 97%
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“…To overcome this drawback, some authors have used revised k-ε models, such as the MMK model, the Durbin model, the Kato-Launder modification, the RNG k-ε model (Zhang and Gu, 2008), the realizable k-ε model (Montazeri and Blocken, 2013) or k-ω based models such as the SST model. Some authors have also made a model comparison (Kim and Patel, 2000;Endo et al, 2005;Guha et al, 2009;Tominaga and Stathopoulos, 2009;Ramponi and Blocken, 2012;Ai et al, 2013).…”
Section: Flow and Turbulence Modelingmentioning
confidence: 97%
“…In addition, a modification to the eddy viscosity is introduced to account for the importance of the transport of the main turbulent shear stress in the prediction of adverse pressure gradient flows. Moreover, in order to limit the well-known excessive generation of turbulence energy in the vicinity of stagnation points as mentioned above, i.e., on the windward surface (Endo et al, 2005;Ai et al, 2013;Guha et al, 2009;Blocken, 2014), we used the Kato and Launder modification to the SST k-ω model, as did Guha et al (2009). This option consists in limiting the turbulence production term P k , by introducing the vorticity rate ˝ in its expression, which is very small at the stagnation points, since the flow is nearly irrotational:…”
Section: Flow and Turbulence Modelingmentioning
confidence: 99%
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“…Elsewhere, the k − results have better residuals than those from the RNG −k − modeling. The k − standard model gives good agreement, but as Endo et al (Endo, 2005) found, the predicted pressure distribution is poor. The mass flow is over-predicted, and the pressure distribution poorly placed by the SST − k − model.…”
Section: Influence Of the Cfd Modeling On Predictedmentioning
confidence: 84%
“…Hu et al show that the structure of ventilating flow is better represented with the SST − k − model than with LES (Wilcox, 1998 andMenter, 1994). The pressure distribution on faces, the pressure extrema and the characteristic lengths are analyzed by Endo et al (Endo, 2005). They conclude that the SST − k − model is not accurate for these three quantities.…”
Section: Influence Of the Cfd Modeling On Predictedmentioning
confidence: 99%