Vorticity Confinement and Advanced Rendering to Compute and Visualize Complex Flows

Wenren, Yonghu; Walter, Jan; Fan, Mingming; Steinhoff, John

doi:10.2514/6.2006-945

Cited by 14 publications

(7 citation statements)

References 9 publications

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“…The University of Tennessee Space Institute and Flow Analysis Inc. developed SAGE (Wenren et al 2006) as an unsteady-flow solver of the Euler equations on uniform structured grids. SAGE uses the vorticity confinement (VC) method to efficiently capture over about two grid cells the vortices and the boundary-layer flow for objects immersed in the grid.…”

Section: Sagementioning

confidence: 99%

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SAGE-PEDD theory manual : modeling windblown snow deposition around buildings

Haehnel¹,

Wenren²,

Allen³

2022

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Numerical modeling of snowdrifting is a useful tool for assessing the impact of building design on operations and facility maintenance. Here we outline the theory for the SAGE-PEDD snowdrift model that has application for determining snowdrift accumulation around buildings. This model uses the SAGE computational fluid dynamics code to determine the flow field in the computational domain. A particle entrainment, dispersion, and deposition (PEDD) model is coupled to SAGE to simulate the movement and deposition of the snow within the computational domain. The report also outlines areas of future development that upgrades to the SAGE-PEDD model should address.

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Section: Sagementioning

confidence: 99%

“…and numerically transports vorticity toward the vortex core (Wenren et al 2006). The continuity equation is satisfied for surface and field confinement; however, the momentum equations are not explicitly satisfied.…”

Section: Field and Surface Confinementmentioning

confidence: 99%

SAGE-PEDD theory manual : modeling windblown snow deposition around buildings

Haehnel¹,

Wenren²,

Allen³

2022

Self Cite

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“…Although the tip vortex is better represented by using VTM as compared to FVM, even this methodology requires the approximation of the ground boundary layer. Wenren et al [10] used a vorticity-confinement method to better resolve the tip vortices in brownout conditions. However, vorticity-confinement methods use empirical factors that may not be easily determined in ground-plane simulations.…”

Section: Introductionmentioning

confidence: 99%

Modeling the Two-Phase Flowfield Beneath a Hovering Rotor on Graphics Processing Units

2015

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The developing brownout cloud beneath a hovering microrotor is simulated using a hybrid free-vortex methodunsteady Reynolds-averaged Navier-Stokes solver coupled with a Lagrangian sediment-tracking algorithm. The present work attempts to examine the capabilities of a high-fidelity computational fluid dynamics analysis together with a sediment-tracking algorithm to analyze the evolution of brownout clouds. Both the single-phase and dual-phase flowfields are simulated and compared to available experimental data. The variation of the phenomenological attributes of the cloud evolution as a function of particle size was analyzed and found to agree with experimental evidence. To enable fast single-desktop simulations, all components of this methodology are designed to run on double-precision, programmable graphics processing units. This hybrid implementation uses a multigranular parallel approach to demonstrate significant performance gains over equivalent single-core central processing unit simulations even when computations involve the solution of sparse implicit systems. Nomenclature A= rotor-disk area, πR 2 , m 2 A R = aspect ratio, R∕c a = speed of sound, m · s −1 C P = rotor power coefficient, P∕ρAΩ 3 R 3 C Poge = rotor power coefficient out-of-ground effect C T = rotor thrust coefficient, T∕ρAΩ 2 R 2 C Toge = rotor thrust coefficient out-of-ground effect c = rotor chord, m d p = particle diameter, μm h = height of rotor aboveground, m M = Mach number, V∕a R = rotor radius, m r = radial distance, m V = velocity, m · s −1 z = distance above the ground plane, m Θ = particle launch angle, rad ρ = flow density, kg · m −3 ρ p = particle density, kg · m −3 ψ = wake age, deg Ω = rotational frequency, rad · s −1

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“…The method has been continually refined and tested during the past decade for configurations such as vortex-solid body interaction (Wang et al, 1995), flow over a cylinder and flow over a block in a channel (Wenren et al, 2001), flow over an automobile (Dietz et al, 2001), three-dimensional cylinder, circle and half-circle (Fan & Steinhoff, 2004). Recently, Wenren et al (2006) implemented Vorticity Confinement into a flow solver to compute rotorcraft brownout using a uniform Cartesian grid. However, the main purpose of their work seemed to be to achieve good visualization of the ground effects, rather than to accurately compute the aerodynamics of rotorcraft.…”

Section: Background Of Vorticity Confinementmentioning

confidence: 99%

Time Spectral Method for Rotorcraft Flow with Vorticity Confinement

Butsuntorn

2008

26th AIAA Applied Aerodynamics Conference

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Vorticity Confinement and Advanced Rendering to Compute and Visualize Complex Flows

Cited by 14 publications

References 9 publications

SAGE-PEDD theory manual : modeling windblown snow deposition around buildings

SAGE-PEDD theory manual : modeling windblown snow deposition around buildings

Modeling the Two-Phase Flowfield Beneath a Hovering Rotor on Graphics Processing Units

Time Spectral Method for Rotorcraft Flow with Vorticity Confinement

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