Computation of the airflow in a pilot scale clean room using K-ε turbulence models

Rouaud, Olivier; Havet, Michel

doi:10.1016/s0140-7007(01)00014-7

Cited by 86 publications

(38 citation statements)

References 9 publications

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“…A flat velocity profile is imposed at the inlet of the domain. The values of turbulent kinetic energy and dissipation rate are computed by considering a turbulent intensity at the inlet equal to 0.05 (Rouaud and Havet 2002). Figure 6 represents the voltage distribution in the whole domain for a gap d=2 cm, an inlet velocity U=0.5 m s −1 .…”

Section: Numerical Resultsmentioning

confidence: 99%

Assessment of the Electrohydrodynamic Drying Process

Ahmedou

Rouaud

Havet

2008

Food Bioprocess Technol

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Industries using energy-intensive processes are being forced to explore ways for reducing their energy consumption. In the food industry, air drying is one of the more energy-consuming processes. To reduce the energy consumption during this operation, alternative processes should be investigated. One promising alternative consists in the electrohydrodynamic (EHD) enhancement of heat and mass transfer. This paper analyses the literature and describes the great potential of this innovative process based on the generation of an electric wind by a corona discharge. The main aspects of this technique are discussed and special emphasis is given on its benefit for food processes. The main part of this paper concerns experimental investigations carried out to assess the EHD enhancement on the drying process. An experimental setup was designed to measure the weight losses on a food product submitted to an electrostatic field and to a cross air flow. Present results confirm that, for a low cross air velocity, the ionic wind leads to an enhancement of the drying rate. The best results are obtained for the smaller distance between the food surface and the corona electrode. Nevertheless, the process is less efficient for a high air velocity. The last part deals with a numerical model that was developed to evaluate the electric parameters and the flow field in turbulent regime. This model provides useful information on the coupled phenomena and permits to explain the experimental observations and to help in designing EHD drying processes. Nomenclature a surface (m 2 ) b ionic mobility (m 2 V −1 s −1 ) d food surface-electrode gap (m) e edge of the wind tunnel (m) E electric field (V m −1 ) F e electric body force (C m −2 s −1 ) g gravity (m s −2 ) I electric current (A) J current density (A m −2 ) k turbulent kinetic energy (m 2 s −2 ) L length of the wind tunnel (m) p pressure (Pa) U velocity vector (m s −1 ) v i ionic wind velocity (m s −1 ) V voltage (V) x distance along surface (m) y height above surface (m) φ diameter (m) ɛ turbulent dissipation rate (m 2 s −3 ) ɛ 0 permittivity of free space (C m −1 V −1 ) Ρ density of air (kg m −3 ) ρ c space charge density (C m −3 ) μ dynamic viscosity of air (Pa s −1 ) μ t turbulent viscosity (Pa s −1 )

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Section: Numerical Resultsmentioning

confidence: 99%

Assessment of the Electrohydrodynamic Drying Process

Ahmedou

Rouaud

Havet

2008

Food Bioprocess Technol

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“…Chen (1995) reviewed and compared eight modified kε models and found that the RNG kε model developed by Yokhot et al (1992) performed best among all the eddy-viscosity models tested for mixed convection flows. Rouaud and Havet (2002) used both standard and RNG turbulence model to simulate the airflow in a food-processing clean room, both models predicted the main features of the airflow and numerical results agreed with experimental measurements, while the RNG kε turbulence model predicted more swirls and more complex trajectories. We adopted RNG kε turbulence model in this study to model the airflow and characterize ventilation effects from different design schemes.…”

Section: Mathematic Modelmentioning

confidence: 65%

Optimization of bathroom ventilation design for an ISO Class 5 clean ward

Yang

et al. 2009

Build. Simul.

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Ventilation is a main method to control the contaminant dispersion within clean wards. In this paper, we investigated the effects of various ventilation designs of the bathroom in an ISO Class 5 clean ward. Specifically, the contaminant dispersion and particle concentrations corresponding to three different ventilation design schemes were characterized and compared using computational fluid dynamics (CFD) analysis. For each design, we examined airflow and particle concentrations for contaminant sources located at two places (i.e., at the toilet seat and on the floor), respectively. Field test was conducted to compare the measured and simulated air velocities and particle concentrations in a hospital clean ward. The implemented CFD modeling of ventilation effects of various designs in this study has proven to accurately characterize airflow and contaminant control in the ventilated space, and has led to optimizing ventilation for the bathroom in an ISO Class 5 clean ward.

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“…Governing equations for the gas phase are based on the continuity equation, N-S equations, energy equation and water vapor diffusion equation. It has been proved that k-ε turbulence models are suitable for predicting indoor air distribution (Chen, 1995;Round and Havet, 2002). Here, a realizable k-ε model is chosen, as turbulent viscosity and turbulent dissipation have been corrected in this model.…”

Section: Airflow and Dropletmentioning

confidence: 99%

Evaporation and Movement of Fine Water Droplets Influenced by Initial Diameter and Relative Humidity

Wang

Yang

Zou

et al. 2016

Aerosol Air Qual. Res.

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Droplets generated in industrial buildings may do harm to the workers, the construction and the environment. Ventilation is often used to control this kind of air-borne contaminants. In order to provide a basis and reference for the efficient ventilation on droplets control, a numerical simulation method is adopted to reveal the evaporation and movement of fine water droplet populations released from a tank in industrial buildings. The variations of diameter and velocity of water droplets with identical initial diameter and velocity were studied. The results showed the evaporation and movement of the droplet populations presented obviously nonuniform distributions, due to vapor concentration and velocity distribution of the air around the droplets. When the droplets were closer to the centerline of the tank, they showed a lower evaporation rate, a larger velocity and a bigger velocity difference between droplets and its surrounding air. The effects of initial diameter and the relative humidity of the ambient air on droplet evaporation and movement were discussed. Compared to the relative humidity of the ambient air, the initial diameter had a more significant effect on the droplet evaporation and movement. The effects of the initial diameter variation (1 µm-50 µm) on the evaporation time variation and the terminal height variation were almost 17 times and 10 times larger than the effects by the relative humidity variation of the ambient air (20%-80%), respectively.

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Computation of the airflow in a pilot scale clean room using K-ε turbulence models

Cited by 86 publications

References 9 publications

Assessment of the Electrohydrodynamic Drying Process

Assessment of the Electrohydrodynamic Drying Process

Optimization of bathroom ventilation design for an ISO Class 5 clean ward

Evaporation and Movement of Fine Water Droplets Influenced by Initial Diameter and Relative Humidity

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