The limiting behaviour of turbulence near a wall

Chapman, Dean R.; Kuhn, G. D.

doi:10.1017/s0022112086000885

Cited by 105 publications

(61 citation statements)

References 29 publications

(42 reference statements)

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“…very close to the wall, as expected from theoretical considerations (Chapman & Kuhn, 1986). Grass (1971) and Krogstad & Antonia (1999) …”

Section: Model-measurement Disagreement and The Turbophoretic Modelsupporting

confidence: 82%

“…Durst et al were able to make high quality measurements very close to the pipe wall by taking great care to minimize wall effects. The two data sets agree well over a range of flow The profiles calculated by DNS follow the quadratic relationship expected from theory (Chapman & Kuhn, 1986).…”

Section: Description Of Turbulent Flow Near Smooth Wallssupporting

confidence: 64%

“…Based on continuity arguments, it is now well accepted that ξ a is proportional to (y + ) 3 in the close vicinity of a wall (Chapman & Kuhn, 1986). The correlation from Davies (1966a) is the only one from Lai & Nazaroff (2000) are plotted in Figure 2.12 and general agreement among the expressions is observed.…”

Section: 41b Eddy Viscositymentioning

confidence: 99%

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Particle deposition in ventilation ducts

Sippola¹

2002

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Exposure to airborne particles is detrimental to human health and indoor exposures dominate total exposures for most people. The accidental or intentional release of aerosolized chemical and biological agents within or near a building can lead to exposures of building occupants to hazardous agents and costly building remediation.Particle deposition in heating, ventilation and air-conditioning (HVAC) systems may significantly influence exposures to particles indoors, diminish HVAC performance and lead to secondary pollutant release within buildings. This dissertation advances the understanding of particle behavior in HVAC systems and the fates of indoor particles by means of experiments and modeling.Laboratory experiments were conducted to quantify particle deposition rates in horizontal ventilation ducts using real HVAC materials. Particle deposition experiments were conducted in steel and internally insulated ducts at air speeds typically found in ventilation ducts, 2-9 m/s. Behaviors of monodisperse particles with diameters in the size range 1-16 µm were investigated. Deposition rates were measured in straight ducts with 1 2 a fully developed turbulent flow profile, straight ducts with a developing turbulent flow profile, in duct bends and at S-connector pieces located at duct junctions. In straight ducts with fully developed turbulence, experiments showed deposition rates to be highest at duct floors, intermediate at duct walls, and lowest at duct ceilings. Deposition rates to a given surface increased with an increase in particle size or air speed. Deposition was much higher in internally insulated ducts than in uninsulated steel ducts. In most cases, deposition in straight ducts with developing turbulence, in duct bends and at S-connectors at duct junctions was higher than in straight ducts with fully developed turbulence.Measured deposition rates were generally higher than predicted by published models.A model incorporating empirical equations based on the experimental measurements was applied to evaluate particle losses in supply and return duct runs. Model results suggest that duct losses are negligible for particle sizes less than 1 µm and complete for particle sizes greater than 50 µm. Deposition to insulated ducts, horizontal duct floors and bends are predicted to control losses in duct systems. When combined with models for HVAC filtration and deposition to indoor surfaces to predict the ultimate fates of particles within buildings, these results suggest that ventilation ducts play only a small role in determining indoor particle concentrations, especially when HVAC filtration is present.However, the measured and modeled particle deposition rates are expected to be important for ventilation system contamination. ChairDate

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“…very close to the wall, as expected from theoretical considerations (Chapman & Kuhn, 1986). Grass (1971) and Krogstad & Antonia (1999) …”

Section: Model-measurement Disagreement and The Turbophoretic Modelsupporting

confidence: 82%

Section: Description Of Turbulent Flow Near Smooth Wallssupporting

confidence: 64%

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Particle deposition in ventilation ducts

Sippola¹

2002

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“…Trias et al to look for solutions with the proper cubic near-wall behavior, 36 i.e., s = 3 (solid lines in Figure 1). This leads to a family of p-dependent eddy-viscosity models,…”

Section: Near-wall Behavior and Other Featuresmentioning

confidence: 99%

“…The second property [Property P1] is the above-mentioned cubic near-wall behavior, i.e., ν e = O( y 3 ). It can be shown that due to the no-slip condition and the incompressibility constraint, the production of turbulent kinetic energy follows a cubic behavior near the wall, 36 i.e., y appropriate that the eddy-viscosity mimics this behavior. As mentioned above, the proposed model also meets this property.…”

Section: Near-wall Behavior and Other Featuresmentioning

confidence: 99%

Building proper invariants for eddy-viscosity subgrid-scale models

Trias¹,

Folch²,

Gorobets

et al. 2015

Physics of Fluids

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Copyright 2015 AIP Publishing. This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing.Direct simulations of the incompressible Navier-Stokes equations are limited to relatively low-Reynolds numbers. Hence, dynamically less complex mathematical formulations are necessary for coarse-grain simulations. Eddy-viscosity models for large-eddy simulation is probably the most popular example thereof: they rely on differential operators that should properly detect different flow configurations (laminar and 2D flows, near-wall behavior, transitional regime, etc.). Most of them are based on the combination of invariants of a symmetric tensor that depends on the gradient of the resolved velocity field, . In this work, models are presented within a framework consisting of a 5D phase space of invariants. In this way, new models can be constructed by imposing appropriate restrictions in this space. For instance, considering the three invariants P GG T , Q GG T , and R GG T of the tensorGG T , and imposing the proper cubic near-wall behavior, i.e., , we deduce that the eddy-viscosity is given by . Moreover, only R GG T -dependent models, i.e., p > - 5/2, switch off for 2D flows. Finally, the model constant may be related with the Vreman’s model constant via ; this guarantees both numerical stability and that the models have less or equal dissipation than Vreman’s model, i.e., . The performance of the proposed models is successfully tested for decaying isotropic turbulence and a turbulent channel flow. The former test-case has revealed that the model constant, C s3pqr , should be higher than 0.458 to obtain the right amount of subgrid-scale dissipation, i.e., C s3pq = 0.572 (p = - 5/2), C s3pr = 0.709 (p = - 1), and C s3qr = 0.762 (p = 0).Peer ReviewedPostprint (published version

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Calculation of complex near‐wall turbulent flows with a low‐Reynolds‐number k‐ϵ model

Koutmos

Kostouros

1995

Numerical Methods in Fluids

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SUMMARYAn improved low-Reynolds-number k-& model has been formulated and tested against a range of DNS (direct numerical simulation) and experimental data for channel and complex shear layer flows. The model utilizes a new form of damping function adopted to account for both wall proximity effects and viscosity influences and a more flexible damping argument based on the gradient of the turbulent kinetic energy on the wall. Additionally, the extra production of the inhomogeneous part of the viscous dissipation near a wall has been added to the dissipation equation with significantly improved results. The proposed model was successfully applied to the calculation of a range of wall shear layers in zero, adverse and favourable pressure gradients as well as backward-facing-step separated flows.

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The limiting behaviour of turbulence near a wall

Cited by 105 publications

References 29 publications

Particle deposition in ventilation ducts

Particle deposition in ventilation ducts

Building proper invariants for eddy-viscosity subgrid-scale models

Calculation of complex near‐wall turbulent flows with a low‐Reynolds‐number k‐ϵ model

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