Particle dispersion and deposition in ventilated rooms: Testing and evaluation of different Eulerian and Lagrangian models

Zhao, Bin; Yang, Chen; Yang, Xudong; Liu, Shuangke

doi:10.1016/j.buildenv.2007.01.005

Cited by 175 publications

(95 citation statements)

References 16 publications

(19 reference statements)

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“…This indicates that small particles behave like a passive tracer gas. This also implies that both the Eulerian and Lagrangian methods should have similar accuracy in predicting transport and dispersion of small particles as shown in Figures 6-8 as already being found by others [15][16][17]. However, the particle concentration was much higher than that of the tracer gas at the locations near the ceiling region in position 3.…”

Section: Discussionsupporting

confidence: 78%

Experimental and numerical investigation of airflow and contaminant transport in an airliner cabin mockup

Zhang

Chen

Mazumdar

et al. 2009

Building and Environment

272

159

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The study of airflow and contaminant transport in airliner cabins is very important for creating a comfortable and healthy environment. This paper shows the results of such a study by conducting experimental measurements and numerical simulations of airflow and contaminant transport in a section of half occupied, twin-aisle cabin mockup. The air velocity and air temperature were measured by ultrasonic and omni-directional anemometers. A gaseous contaminant was simulated by a tracer gas, sulfur hexafluoride or SF 6 , and measured by a photoacoustic multi-gas analyzer. A particulate contaminant was simulated by 0.7 μm Di-Ethyl-HexylSebacat (DEHS) particles and measured by an optical particle sizer. The numerical simulations used the Reynolds averaged Navier-Stokes equations based on the RNG k-ε model to solve the air velocity, air temperature, and gas contaminant concentration; and employed a Lagrangian method to model the particle transport. The numerical results quantitatively agreed with the experimental data while some remarkable differences exist in airflow distributions. Both the experimental measurements and computer simulations were not free from errors. A complete and accurate validation for a complicated cabin environment is challenging and difficult.

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Section: Discussionsupporting

confidence: 78%

Experimental and numerical investigation of airflow and contaminant transport in an airliner cabin mockup

Zhang

Chen

Mazumdar

et al. 2009

Building and Environment

272

159

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“…The drift flux model [13] integrates the gravitational settling, convection and diffusion effects of particles into the governing equation of particles. In the drift flux model, the governing equation for particle transport in turbulent flow field is expressed as:…”

Section: Drift Flux Modelmentioning

confidence: 99%

“…However, the computational cost of the Lagrangian method limits its application in smoke simulations within large-scale fire enclosures as statistically stable particle concentrations require a large number of particle tracks [13]. Compared with the expensive computational requirement of the Lagrangian method, the computational cost of the Eulerian method for simulating particle movement is significantly lower.…”

Section: Introductionmentioning

confidence: 99%

Simulating Smoke Transport in Large Scale Enclosure Fires Using a Multi-Particle-Size Model

Hu¹,

Wang²,

Jia³

et al. 2011

Fire Safety Science - Proceedings of the 10th International Sym

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In computational fluid dynamics (CFD) based fire simulation, the particle-laden smoke is usually assumed to be in a gaseous state. This is due to the assumption that most of the smoke particles have diameters less than about 2.0 µm and so their settling velocities can be ignored compared with the intensive turbulent fire gas flow. This simplification can lead to severely under-predicted smoke levels in the lower layer at remote locations from the fire source. This problem is addressed in this paper through the development of a multiparticle-size model which takes into consideration the uneven mass size distributions of smoke particles. The model divides the smoke particles into three groups with various diameter ranges. The transport of smoke particles in each group is represented by a governing equation, in which the gravitational force is addressed by adding a correction into the convection term. The efficiency of the model to reproduce smoke transport is demonstrated by simulating a large scale PVC cable fire experiment conducted in a long corridor. Compared with a conventional smoke transport model, the new model is shown to be better able of reproducing the measured experimental smoke data and the recorded visibilities.KEYWORDS: smoke transport, smoke particle, CFD, drift flux model, large-scale enclosure fire. NOMENCLATURE LISTING

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“…The major difference between Eulerian and Lagrangian models lies in the fact that the Eulerian method treats particles as a continuum through a continuous scalar field determined by writing and solving a particle transport equation (Gouesbet and Berlemont 1999), whereas the Lagrangian method considers two different phases: a fluid phase treated as a continuum by solving the time-averaged Navier-Stokes equations, and a discrete particle phase requiring the resolution of an equation of motion resulting from various forces acting on each individual particle to obtain a single particle trajectory (Zhao et al 2008). The Eulerian method has the advantage of being relatively straightforward because the mean particle concentration is calculated directly by solving an advection-diffusion conservation equation in a turbulent flow on the same grid, and because computational time is significantly reduced as there is no individual particle tracking required, in contrast with Lagrangian modeling approaches (Dupont et al 2006;Lai and Chen 2007a).…”

Section: Introductionmentioning

confidence: 99%

“…Many authors have compared the Lagrangian and Eulerian approaches and tested their respective ability to assess particle dispersion and deposition indoors for different turbulent flow configurations. According to Gouesbet and Berlemont (1999), Zhang and Chen (2007), and Zhao et al (2008), there is no clear-cut way to conclude which is the better of the two models today, as each imposes its own fundamental assumptions, often leading to fully comparable predictions. However, in any case, regardless of the models used, proper treatment of the near-wall flow is absolutely critical to obtaining accurate particle deposition prediction, since fluctuating near-wall velocities are highly anisotropic, with the component normal to the wall being smaller than the components in the other two directions (Lai and Chen 2007b).…”

Section: Introductionmentioning

confidence: 99%

Toward Quantitative CFD Prediction of Contaminant Particle Deposition against Surfaces in Large Forced-Ventilation Food Plants

Chorel

Kondjoyan

Mirade

2010

Aerosol Science and Technology

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This article discusses the application of a computational fluid dynamics (CFD) approach for constructing a numerical methodology based on Reynolds-Averaged Navier-Stokes (RANS) equations in order to accurately determine particle deposition rates against surfaces subjected to a low-velocity turbulent airflow. We began by studying a horizontal duct flow configuration and validating the numerical output for airflow pattern and particle deposition rate predictions against published numerical data. The main outcome of this first part of the study was that when starting from a one-way coupling Lagrangian formulation, accurate prediction of particle deposition rates strictly requires the construction of a sufficiently fine mesh (characterized by a dimensionless "distance to wall" criterion y + lower than 4) and the use of a turbulence model accounting for turbulence anisotropy in combination with a near-wall "two-layer zonal" boundary condition. The CFD methodology set up was then used to predict airflow patterns together with airborne deposition of spherical 1-50 µm particles against all the surfaces in an 87 m 3 ventilated cold room filled with 9 big rectangular parallelepipeds. The results demonstrated close agreement in air velocity predictions and showed particle deposition rates varying with both room wall surface type and orientation and with particle diameter due to the different physical phenomena involved. This paper is the first attempt to predict particle deposition in such a large volume, corresponding to a food-processing environment.

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Particle dispersion and deposition in ventilated rooms: Testing and evaluation of different Eulerian and Lagrangian models

Cited by 175 publications

References 16 publications

Experimental and numerical investigation of airflow and contaminant transport in an airliner cabin mockup

Experimental and numerical investigation of airflow and contaminant transport in an airliner cabin mockup

Simulating Smoke Transport in Large Scale Enclosure Fires Using a Multi-Particle-Size Model

Toward Quantitative CFD Prediction of Contaminant Particle Deposition against Surfaces in Large Forced-Ventilation Food Plants

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