Stationary vortices attached to flat roofs

Tryggeson, Henrik; Lyberg, Mats D.

doi:10.1016/j.jweia.2009.09.001

Cited by 13 publications

(5 citation statements)

References 22 publications

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“…Stability at low grid resolutions is ensured by numerical viscosity, which we shall now assess. As an approximated method, we propose to compare the classical vorticity ω decay in incompressible fluid at rest [43][44][45]…”

Section: Isentropic Vortex Convection By a Uniform Flowmentioning

confidence: 99%

Hybrid recursive regularized thermal lattice Boltzmann model for high subsonic compressible flows

Feng

Boivin

Jacob

et al. 2019

Journal of Computational Physics

107

146

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A thermal lattice Boltzmann model with a hybrid recursive regularization (HRR) collision operator is developed on standard lattices for simulation of subsonic and sonic compressible flows without shock. The approach is hybrid: mass and momentum conservation equations are solved using a lattice Boltzmann solver, while the energy conservation is solved under entropy form with a finite volume solver. The defect of Galilean invariance related to Mach number is corrected by the third order equilibrium distribution function, supplemented by an additional correcting term and hybrid recursive regularization. The proposed approach is assessed considering the simulation of i) an isentropic vortex convection, ii) a two dimensional acoustic pulse and iii) non-isothermal Gaussian pulse with Ma number in range of 0 to 1. Numerical simulations demonstrate that the flaw in Galilean invariance is effectively eliminated by the compressible HRR model. At last, the compressible laminar flows over flat plate at Ma number of 0.3 and 0.87, Reynolds number of 10 5 are considered to validate the capture of viscous and diffusive effects.

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Section: Isentropic Vortex Convection By a Uniform Flowmentioning

confidence: 99%

Hybrid recursive regularized thermal lattice Boltzmann model for high subsonic compressible flows

Feng

Boivin

Jacob

et al. 2019

Journal of Computational Physics

107

146

View full text Add to dashboard Cite

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“…The world has been rapidly urbanising for the past five decades, with~54% of the population currently living in urban areas, expected to reach~66% by 2050 [1]. As a result, cities are transforming with more high-rise buildings being planned to cope with the increasing dwelling demand, living mechanism, size and fluctuation of conical vortices have been provided investigating the effect of incident winds [25,26] and the shape of the building [27,28], leading to the development of analytical models for conical vortices on low-rise buildings [29][30][31].…”

Section: Introductionmentioning

confidence: 99%

On the Flow over High-rise Building for Wind Energy Harvesting: An Experimental Investigation of Wind Speed and Surface Pressure

et al. 2020

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The human migration from rural to urban areas has triggered a chain reaction causing the spiking energy demand of cities worldwide. High-rise buildings filling the urban skyline could potentially provide a means to improve the penetration of renewable wind energy by installing wind turbines at their rooftop. However, the above roof flow region has not received much attention and most results deal with low-rise buildings. This study investigates the flow pattern above the roof of a high-rise building by analysing velocity and pressure measurements performed in an atmospheric boundary layer wind tunnel, including four wind directions and two different roof shapes. Comparison of the surface pressure patterns on the flat roof with available low-rise building studies shows that the surface pressure contours are consistent for a given wind direction. At 0° wind direction, a separation bubble is detected, while cone vortices dominate at 30° and 45°. The determining factor for the installation of small wind turbines is the vicinity to the roof. Thus, 45° wind direction shows to be the most desirable angle by bringing the substantial amplification of wind and keeping the turbulence intensity low. Decking the roof creates favourable characteristics by overcoming the sensitivity to the wind direction while preserving the speed-up effect.

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“…Previous work (e.g., Lim et al, 2007) has demonstrated the Re-dependence (that can persist well-beyond Re > 2 × 10 4 ) when quantifying peak suction pressures on sharp-edged bluff bodies oriented at 45 • to the approach flow; which is the wind direction considered in this study. This wind orientation promotes the development of strong (and relatively steady) "delta-wing type" conical vortices that originate at roof corners and extend along line inclines of ∼11-14 • relative to roof edges, where smaller angles are associated with larger Re numbers (Tryggeson and Lyberg, 2010). The structure of conical vortices has been shown to strongly affect Re, which partly explains FIGURE 11 | Area-averaged peak pressures from six corner roof taps (Tap IDs 215,216,301,314,315,and 316) as a function of freestream turbulence: (A) 1:50, (B) 1:30, and (C) 1:20.…”

Section: Discussionmentioning

confidence: 99%

Predicting Roof Pressures on a Low-Rise Structure From Freestream Turbulence Using Artificial Neural Networks

Fernández-Cabán

Masters

Phillips

2018

Front. Built Environ.

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This paper presents a generalized approach for predicting (i.e., interpolating) the magnitude and distribution of roof pressures near separated flow regions on a low-rise structure based on freestream turbulent flow conditions. A feed-forward multilayer artificial neural network (ANN) using a backpropagation (BP) training algorithm is employed to predict the mean, root-mean-square (RMS), and peak pressure coefficients on three geometrically scaled (1:50, 1:30, and 1:20) low-rise building models for a family of upwind approach flow conditions. A comprehensive dataset of recently published boundary layer wind tunnel (BLWT) pressure measurements was utilized for training, validation, and evaluation of the ANN model. On average, predicted ANN peak pressure coefficients for a group of pressure taps located near the roof corner were within 5.1, 6.9, and 7.7% of BLWT observations for the 1:50, 1:30, and 1:20 models, respectively. Further, very good agreement was found between predicted ANN mean and RMS pressure coefficients and BLWT data.

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Stationary vortices attached to flat roofs

Cited by 13 publications

References 22 publications

Hybrid recursive regularized thermal lattice Boltzmann model for high subsonic compressible flows

Hybrid recursive regularized thermal lattice Boltzmann model for high subsonic compressible flows

On the Flow over High-rise Building for Wind Energy Harvesting: An Experimental Investigation of Wind Speed and Surface Pressure

Predicting Roof Pressures on a Low-Rise Structure From Freestream Turbulence Using Artificial Neural Networks

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