CFD prediction of cooling tower drift

Meroney, Robert N.

doi:10.1016/j.jweia.2006.01.015

Cited by 55 publications

(38 citation statements)

References 22 publications

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“…Riddle et al, 2004, compared CFD results with the predictions from the Atmospheric Dispersion Modelling System (ADMS) in geometrically complex situations as the case of buildings in close proximity. Meroney, 2006, developed a computational fluid dynamics model to simulate cooling tower plume dispersion and drift. He predicted drift deposition levels downwind a cooling tower.…”

Section: Introductionmentioning

confidence: 99%

On the influence of psychrometric ambient conditions on cooling tower drift deposition

Lucas

Martínez

Ramírez

et al. 2010

International Journal of Heat and Mass Transfer

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Water drift emitted from cooling towers is objectionable for several reasons, mainly due to human health reasons. A numerical model to study the influence of psychrometric ambient conditions on cooling tower drift deposition was developed. The mathematical model presented, consisting of two coupled sets of conservation equations for the continuous and discrete phases, was incorporated in the general purpose CFD code Fluent. Both experimental plume performance and drift deposition were employed to validate the numerical results. This study shows the influence of variables like ambient dry bulb temperature, ambient absolute humidity and droplet exit temperature from cooling tower on the drift evaporation (and therefore deposition) and on the zone affected by the cooling tower. The stronger effect detected corresponds to the ambient dry bulb temperature.When a higher ambient temperature was present, deposition was lower (evaporation was therefore higher) and the zone affected by the cooling tower was smaller. The influence of the other two variables included in the study was weaker than the one corresponding to the dry bulb ambient temperature. A high level of ambient absolute humidity increased drift deposition and also the size of the zone affected by the cooling tower. Finally, a high level of droplet exit temperature decreased deposition and increased the zone affected by the cooling tower.Keywords: Cooling towers, drift, legionaries' disease, CFD, deposition.

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Section: Introductionmentioning

confidence: 99%

On the influence of psychrometric ambient conditions on cooling tower drift deposition

Lucas

Martínez

Ramírez

et al. 2010

International Journal of Heat and Mass Transfer

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“…Meroney [3] reviewed experimental and numerical research related to the flow around and from natural and mechanical draft cooling towers. A number of previous researchers have used CFD to calculate cooling tower plume rise, dispersion, moisture visibility, and building interaction.…”

Section: Prediction Of Cooling Tower Plume Behaviormentioning

confidence: 99%

“…No CFD calculations were found in the literature that predicted drift deposition levels downwind of cooling towers. Hence, Meroney [3] examined the use of a Lagrangian discrete particle method to predict drift measured during the 1977 Chalk Point Dye Tracer Experiment. His results confirmed that such an approach could predict plume rise, ground concentrations, and deposition magnitudes for an isolated cooling tower situation.…”

Section: Prediction Of Cooling Tower Plume Behaviormentioning

confidence: 99%

“…A review of the literature by Meroney [3] produced nine sets of data for the cumulative mass fraction distributions of droplets. The cumulative mass fraction for these cases tended to decrease exponentially with increasing particle diameter; hence, the data were fit to a Rosin-Rammler particle distribution of the form:…”

Section: Discrete Phase Modelingmentioning

confidence: 99%

“…Prediction of drift deposition is generally provided by analytic models such as the US Environmental Protection Agency approved ISCST3 (Industrial Source Complex Short Term Version 3) [1] or SACTI (Seasonal-Annual Cooling Tower Impact) [2] codes; however, these codes are less suitable when cooling towers are located midst taller structures and buildings. A computational fluid dynamics (CFD) code including Lagrangian prediction of the gravity driven but stochastic trajectory descent of droplets was previously considered and compared to data from the 1977 Chalk Point Dye Tracer Experiment [3]. The CFD program predicted plume rise, surface concentrations, plume centerline concentrations and surface drift deposition for the Chalk Point study within the bounds of field experimental accuracy.…”

Section: Introductionmentioning

confidence: 99%

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Protocol for CFD prediction of cooling-tower drift in an urban environment

Meroney

2008

Journal of Wind Engineering and Industrial Aerodynamics

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A computational fluid dynamics (CFD) code including Lagrangian prediction of the gravity driven but stochastic trajectory descent of droplets is considered to predict plume rise and surface drift deposition from mechanical draft cooling towers. CFD drift deposition calculations are performed for a specific urban cooling tower situation with and without the urban buildings surrounding the cooling tower complex present to produce a set of multiplicative factors that could be used to correct seasonal or annual predictions for the presence of large urban structures.

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Urban emissions of water vapor in winter

et al. 2017

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Elevated water vapor (H2Ov) mole fractions were occasionally observed downwind of Indianapolis, IN, and the Washington, D.C.‐Baltimore, MD, area during airborne mass balance experiments conducted during winter months between 2012 and 2015. On days when an urban H2Ov excess signal was observed, H2Ov emission estimates range between 1.6 × 104 and 1.7 × 105 kg s−1 and account for up to 8.4% of the total (background + urban excess) advected flow of atmospheric boundary layer H2Ov from the urban study sites. Estimates of H2Ov emissions from combustion sources and electricity generation facility cooling towers are 1–2 orders of magnitude smaller than the urban H2Ov emission rates estimated from observations. Instances of urban H2Ov enhancement could be a result of differences in snowmelt and evaporation rates within the urban area, due in part to larger wintertime anthropogenic heat flux and land cover differences, relative to surrounding rural areas. More study is needed to understand why the urban H2Ov excess signal is observed on some days, and not others. Radiative transfer modeling indicates that the observed urban enhancements in H2Ov and other greenhouse gas mole fractions contribute only 0.1°C d−1 to the urban heat island at the surface. This integrated warming through the boundary layer is offset by longwave cooling by H2Ov at the top of the boundary layer. While the radiative impacts of urban H2Ov emissions do not meaningfully influence urban heat island intensity, urban H2Ov emissions may have the potential to alter downwind aerosol and cloud properties.

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CFD prediction of cooling tower drift

Cited by 55 publications

References 22 publications

On the influence of psychrometric ambient conditions on cooling tower drift deposition

On the influence of psychrometric ambient conditions on cooling tower drift deposition

Protocol for CFD prediction of cooling-tower drift in an urban environment

Urban emissions of water vapor in winter

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