Extension to various thermal boundary conditions of the elliptic blending model for the turbulent heat flux and the temperature variance

Mangeon, Gaëtan; Benhamadouche, Sofiane; Wald, Jean-François; Manceau, Rémi

doi:10.1017/jfm.2020.683

Cited by 8 publications

(1 citation statement)

References 40 publications

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“…Besides walls, mean flow acceleration, deceleration and rotation can weaken or increase turbulent stresses (Durbin 2018) and thus cause a change of the flow regime. Near-wall modelling is an important factor when simulating surface heat transfer (Kriegel 2005;Mangeon et al 2020) and flow separation from curved surfaces .…”

Section: Low Reynolds Number Turbulence Modellingmentioning

confidence: 99%

Turbulence model performance for ventilation components pressure losses

Tawackolian

Kriegel

2021

Build. Simul.

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This study looks to find a suitable turbulence model for calculating pressure losses of ventilation components. In building ventilation, the most relevant Reynolds number range is between 3×104 and 6×105, depending on the duct dimensions and airflow rates. Pressure loss coefficients can increase considerably for some components at Reynolds numbers below 2×105. An initial survey of popular turbulence models was conducted for a selected test case of a bend with such a strong Reynolds number dependence. Most of the turbulence models failed in reproducing this dependence and predicted curve progressions that were too flat and only applicable for higher Reynolds numbers. Viscous effects near walls played an important role in the present simulations. In turbulence modelling, near-wall damping functions are used to account for this influence. A model that implements near-wall modelling is the lag elliptic blending k-ε model. This model gave reasonable predictions for pressure loss coefficients at lower Reynolds numbers. Another example is the low Reynolds number k-ε turbulence model of Wilcox (LRN). The modification uses damping functions and was initially developed for simulating profiles such as aircraft wings. It has not been widely used for internal flows such as air duct flows. Based on selected reference cases, the three closure coefficients of the LRN model were adapted in this work to simulate ventilation components. Improved predictions were obtained with new coefficients (LRNM model). This underlined that low Reynolds number effects are relevant in ventilation ductworks and give first insights for suitable turbulence models for this application. Both the lag elliptic blending model and the modified LRNM model predicted the pressure losses relatively well for the test case where the other tested models failed.

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Section: Low Reynolds Number Turbulence Modellingmentioning

confidence: 99%