Eulerian and Lagrangian predictions of particulate two-phase flows: a numerical study

Durst, F.; Miloievic, D.; Schönung, B.

doi:10.1016/0307-904x(84)90062-3

Cited by 275 publications

(117 citation statements)

References 9 publications

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“…By solving particle trajectories for particles from several different initial locations, airflow with particles can be simulated and information about particle deposition can be obtained. (Durst et al, 1984;Gouesbet & Berlemont, 1999). In general, Lagrangian simulations require less conceptual modeling and capture more of the fundamental physics involved in particle motion, but at a much greater computational cost.…”

Section: Methods: Empiricism Eulerian Models and Lagrangian Simulationsmentioning

confidence: 99%

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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Section: Methods: Empiricism Eulerian Models and Lagrangian Simulationsmentioning

confidence: 99%

Particle deposition in ventilation ducts

Sippola¹

2002

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“…The Two-Fluid mode1 treats particles as a second fluid with a distinct velocity froni the gas-phase, (Durst et al (1984)). The particle phase is treated as a continuum without a pressure term in the equation of motion since the pressure gradient effects are already included in the drag coefficient.…”

Section: Two-fluid Modelsmentioning

confidence: 99%

A Comparison of Stochastic Separated Flow Models for Particle Dispersion in Turbulent Flows

Hennick¹,

Lightstone²

1999

Energy Fuels

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This manuscript has been reproduoed from the microfilm master. UMI films the text directly from the original or copy submitied. Thus, some thesis and dissertation copies are in typewriter face, while others may be from any type of cornputer printer.The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, pnnt bleedthrough, substandard margins, and improper alignment can adversely affect reproduction.In the unlikely event that the author did not send UMI a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion.Oversize materials (e-g., maps, drawings, &arts) are reproduced by sectioning the original, beginning at the upper lefi-hand corner and continuing from left to right in equal sections with small overlaps. Each original is also photographed in one exposure and is included in reduced fom at the back of the book.Photographs included in the original manuscript have been reproduced xerographically in this copy. Higher quality 6 x 9" black and white photographic prints are available for any photographs or illustrations appearing in this wpy for an additional charge. Contact UMI directly to order. This thesis investigates Stochastic Separated Flow (SSF) models for particle dispersioii iu turbulent flows. A new model is presented that incorporates a temporal and a spatial autocorrelation in the description of the fiuctuating component of the turbulent gas-phase velocity. This mode1 and four SSF niodels ai-aiIabIe in the literarure are el-aliiat~cl ailalytically and b -cornparing predictions wit h the grid-generated turbulence esperimenr 3 of Snyder andLumley (1971). andWells andStock (1983). Results are discuîsed aiid deficiencies in the models explored. The nen-model of Hennick and Lightstone conipeiisares for the crossing trajectory effecr xith the inclusion of a spatial correlarioii basecl on the relative velocity of the particle and the timestep employed. Promisirig resuirs arp obtained using this model.

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“…Below, a brief description of the two methods is given. For further details and a comparison of the results of the two methods the reader is referred to the following literature: Durst et al [29], Crowe et al [21], Loth [86] and Wachem and Almstedt [140].…”

Section: Methodsmentioning

confidence: 99%

Eulerian method for ice crystal icing in turbofan engines

Norde¹

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Eulerian and Lagrangian predictions of particulate two-phase flows: a numerical study

Cited by 275 publications

References 9 publications

Particle deposition in ventilation ducts

Particle deposition in ventilation ducts

A Comparison of Stochastic Separated Flow Models for Particle Dispersion in Turbulent Flows

Eulerian method for ice crystal icing in turbofan engines

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