• Andreopoulos, J., 1989a: Wind tunnel experiment on cooling tower plumes: Part 1—In uniform crossflow. J. Heat Transfer, 111, 941948.

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  • Andreopoulos, J., 1989b: Wind tunnel experiment on cooling tower plumes: Part 2—In a nonuniform crossflow of boundary layer type. J. Heat Transfer, 111, 949955.

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  • Becker, B. R., , W. E. Stewart, , and T. M. Walter, 1989: A numerical model of cooling tower plume recirculation. Math. Comput. Modell., 12, 799819.

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  • Guo, D. P., , R. T. Yao, , and Q. D. Qiao, 2010: Numerical and wind tunnel simulation study on impacts of buildings on dispersion of pollutants. J. Exp. Fluid Mech.,24, 1621.

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  • Hanna, S. R., , G. A. Briggs, , and J. R. P. Hosker, 1982: Handbook on atmospheric diffusion. U.S. Department of Energy, 102 pp.

  • Hoult, D. P., , and J. C. Weil, 1972: Turbulent plume in a laminar cross flow. J. Atmos. Environ.,6, 513531.

  • Jain, S. C., , and J. F. Kennedy, 1978: Modeling near-field behavior of mechanical draft cooling tower plumes, environmental effects of cooling tower plumes. WRRC Special Rep. 9, 13–30.

  • Janicke, U., , and L. Janicke, 2001: A three-dimensional plume rise model for dry and wet plumes. J. Atmos. Environ.,35, 877–890.

  • Michioka, T., , A. Sato, , T. Kanzaki, , and K. Sada, 2007: Wind tunnel experiment for predicting a visible plume region from a wet cooling tower. J. Wind Eng. Ind. Aerodyn.,95, 741–754.

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    • Export Citation
  • Moore, D. J., 1974: The prediction of the rise of cooling tower plumes. J. Atmos. Environ.,8, 403–406.

  • Overcamp, T. J., , and T. Ku, 1986: Effect of a virtual origin correction on entrainment efficient as determined from observations of plume rise. J. Atmos. Environ.,20, 293–300.

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    • Export Citation
  • Policastro, A. J., 1994: A model for seasonal and annual cooling tower impacts. J. Atmos. Environ., 28, 379–395.

  • Policastro, A. J., , and M. Wastag, 1981: Studies on mathematical models for characterizing plume and drift behavior from cooling tower. Volume 1: Review of European research. EPRI Interim Rep. CS-1683, 192 pp.

  • Yao, R. T., , M. S. Zhang & , and S. W. Tao, 1997: Experimental investigations on the effects of architectural complex on the site of Qinshan phase II NPP project on the dispersion of gaseous radioactive emissions. J. Radiat. Prot.,17, 192–199.

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    The wind tunnel experimental model.

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    Sketch map of multipoint sampling tracer measurement system in wind tunnel (aerial sampling).

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    Dependence of (a) normalized velocity profiles and (b) longitudinal turbulent intensity on height z.

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    Psychrometric chart. The curved line is the variation of saturation specific humidity with temperature.

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    Definitions of length, extent, and rise of visible plume from the cooling tower.

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    The changes of (a) normalized velocity and (b) longitudinal turbulent intensity measured at different locations.

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    Comparison of the results of present wind tunnel data and EDF data for the visible plume region; D is the cooling tower exit diameter.

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    The rise of the cooling tower plume with downwind distance: comparison of the wind tunnel data with Briggs's numerical results.

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Wind Tunnel Experiment for Predicting a Visible Plume Region from a Nuclear Power Plant Cooling Tower

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  • 1 Department of Environment Science and Engineering, Taiyuan University of Science and Technology, Taiyuan, China
  • | 2 China Institute for Radiation Protection, Taiyuan, China
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Abstract

This paper introduces a wind tunnel experiment to study the effect of the cooling tower of a nuclear power plant on the flow and the characteristics of visible plume regions. The relevant characteristics of the flow field near the cooling tower, such as the plume rise and the visible plume region, are compared with the results of previous experimental data from Électricité de France (EDF) and the Briggs formulas. The results show that the wind tunnel experiment can simulate the top backflow of the cooling tower and the rear cavity regions among others. In the near-wake region, including the recirculation cavity, mean velocity decreases and turbulence intensity increases significantly. The maximum turbulence intensity observed is 0.5. In addition, the disturbed flow extent of the cooling tower top reaches 1.5 times the cooling tower height. Analysis of the visible plume region shows that the wind tunnel experiment can simulate the variation of a visible plume region. The results are consistent with the wind tunnel experiment of EDF. Moreover, the plume rise analysis shows that the wind tunnel experiment data are in agreement with the Briggs formulas for 50–200 m. As a whole, the proposed wind tunnel experiment can simulate the flow field variation of the visible plume region and the plume rise around the buildings with reasonable accuracy.

Corresponding author address: Guo Dong-Peng, Department of Environment Science and Engineering, Taiyuan University of Science and Technology, Waliu Road 66, Taiyuan 030024, China. E-mail: guodp@126.com

Abstract

This paper introduces a wind tunnel experiment to study the effect of the cooling tower of a nuclear power plant on the flow and the characteristics of visible plume regions. The relevant characteristics of the flow field near the cooling tower, such as the plume rise and the visible plume region, are compared with the results of previous experimental data from Électricité de France (EDF) and the Briggs formulas. The results show that the wind tunnel experiment can simulate the top backflow of the cooling tower and the rear cavity regions among others. In the near-wake region, including the recirculation cavity, mean velocity decreases and turbulence intensity increases significantly. The maximum turbulence intensity observed is 0.5. In addition, the disturbed flow extent of the cooling tower top reaches 1.5 times the cooling tower height. Analysis of the visible plume region shows that the wind tunnel experiment can simulate the variation of a visible plume region. The results are consistent with the wind tunnel experiment of EDF. Moreover, the plume rise analysis shows that the wind tunnel experiment data are in agreement with the Briggs formulas for 50–200 m. As a whole, the proposed wind tunnel experiment can simulate the flow field variation of the visible plume region and the plume rise around the buildings with reasonable accuracy.

Corresponding author address: Guo Dong-Peng, Department of Environment Science and Engineering, Taiyuan University of Science and Technology, Waliu Road 66, Taiyuan 030024, China. E-mail: guodp@126.com
Keywords: Air pollution

1. Introduction

According to the overall planning of nuclear power development in China, a number of nuclear power plants will be built at the seaside or on riverbanks. In addition, recently the possibility of an inland nuclear power plant has also been considered and site selections and demonstrations for the same have been carried out. Unlike seaside sites, inland nuclear power plants use secondary circulation cooling from a natural draft cooling tower. The process of heat exchange between the cool air and the hot water inside the cooling tower, accompanied by the rise of air, may produce a great deal of water vapor. This water vapor is released into the atmosphere, and it becomes a visible plume during the process of the heat exchange between the water vapor and the air in the surrounding environment with a certain temperature difference. This visible plume may have radioactive contaminants discharged from the chimney and may form precipitation in the downwind direction of the cooling tower. Under certain conditions the visible plume may fall to the ground and freeze, causing wet deposition of radioactivity and thus increasing the risk of near-field radioactivity from ground deposition.

Previous research on the diffusion of a plume from a cooling tower was mainly focused on the visible plume region from nuclear power plants and the impact on the distribution of radioactive material that comes from the chimneys around the nuclear equipment (Policastro 1994; Hanna et al. 1982). These studies include 39 groups of field test data of power plants with a single cooling tower, such as Chalk Point and Paradise, 26 groups of field test data of power plants with multiple cooling towers, such as Neurath and Amos, and meteorological observations of environmental impacts of the plume from the Ratcliffe power plant cooling tower (Policastro 1994).

Along with the field tests, corresponding wind tunnel experimental studies have also been carried out. Andreopoulos (1989a,b) studied the interrelationships of the wake of plumes from the cooling tower and the plume disturbance in a wind tunnel experiment. In the experiment, the turbulent intensity downwind of the cooling tower increased significantly, and high turbulent intensity was observed until it reached a distance of 6–8 times the diameter of the cooling tower in the downstream direction. Results show that the rise of the plume from the cooling tower is related to the wake region of the cooling tower. Jain and Kennedy (1978) studied the relationship between the plume from a mechanical draft cooling tower and the wind direction in a wind tunnel experiment. They found that a definite relation exists between the plume from the cooling tower and the wake for different wind directions. Michioka et al. (2007) studied the visible plume region of a cooling tower and thermal conversion laws in their wind tunnel laboratories by replacing the plume from a mechanical draft cooling tower with a tracer gas. Their experimental results agreed with the data from the previous field experiments. Becker et al. (1989) studied the plume diffusion laws in the backflow region of cooling towers and pointed out that the plume from cooling towers might be heavily entrained into the backflow region. Janicke and Janicke (2001) proposed a set of formulas to estimate the visible plume region of cooling towers. However, the visible plume region can only be estimated if the sensible heat, latent heat, and hot water content of the plume at different positions are known. Their research showed that the plume rise from cooling tower is mainly related to air velocity, plume emission rate, and densimetric Froude number. A common model that estimates the plume rise and visible plume region of cooling tower often ignores the impacts of plume evaporation and condensation.

Moore (1974) combined a large number of field observations, experimental results, and theoretical results and deduced a formula to calculate the plume rise from cooling towers and the length of the visible plume region. He then compared the calculations from the formula with field observations and test results. Results showed that the formula enabled a better calculation of the plume rise from cooling tower and the length of visible plume region, with relative deviations from field tests within 10%. Also, Moore (1974) found that the plume rise from the cooling tower and the extent of the visible plume region were mainly related to air velocity and stability. Meanwhile, Hanna et al. (1982) also deduced the calculation formula of the rise height and length of visible plume. However, the formula can provide only the maximum plume rise from a cooling tower and the length of visible plume region.

In China, there has been no previous research on the visible plume region of cooling towers. The inland nuclear power plant design considered in the current study will adopt a very large type of cooling tower with staggering environmental impacts. The present paper investigates the site selection of an inland nuclear power plant in China and deals with the impacts of the architectural complex, including the cooling tower, as well as the behavior of the rise height of visible plume from the cooling tower in wind tunnel simulation tests.

2. Experimental method

a. Test apparatus and model

The current experiment was done in the Environmental Wind Tunnel Laboratory of the China Institute for Radiation Protection. The wind tunnel used is a direct-flow air-blowing type. The test section is 17 m long, 1.5 m wide, and 1–1.4 m high, with wind velocities of 0.2–9 m s−1. A neutral boundary layer was developed by adjusting a fence at the entrance to the test section, and the required velocity profile and turbulence distribution were formed at the test section by artificial roughness elements.

The present paper describes a wind tunnel study of the effect of the number 2 cooling tower on the flow and the characteristics of a visible plume region on the Pengzhe nuclear power plant (NPP) site. The present research mainly simulates the neutral atmospheric boundary layer flow and establishes a wind tunnel experimental model in which the location of the number 2 cooling tower is at the center. The modeled region extends the equivalent of 5 km from the center location. Figure 1 shows the wind tunnel experimental model.

Fig. 1.
Fig. 1.

The wind tunnel experimental model.

Citation: Journal of Applied Meteorology and Climatology 53, 2; 10.1175/JAMC-D-13-0153.1

b. Simulation method

The simulation of the plume from the cooling tower in the wind tunnel is one of the key objectives in the present study. The wind tunnel plume mixture consists of carbon monoxide (CO), helium (He), and air. The density ratio of the mixture is adjusted such that the momentum flux ratio of the thermal plume from the modeled cooling tower and the Froude number are consistent with the actual conditions. Thus, the behavior of the actual plume from the cooling tower (including the momentum plume rise and the buoyant plume rise, but not including condensation/evaporation effects) is closely reproduced. Helium provides the appropriate buoyancy, and CO acts as a tracer gas. The simulated emission systems include a high-pressure CO cylinder, a helium cylinder, an air cylinder, an air pump, a flowmeter and mixer, gas storage, and connecting pipe systems. Figure 2 shows the block diagram of the multipoint sampling tracer measurement system in the wind tunnel (aerial sampling).

Fig. 2.
Fig. 2.

Sketch map of multipoint sampling tracer measurement system in wind tunnel (aerial sampling).

Citation: Journal of Applied Meteorology and Climatology 53, 2; 10.1175/JAMC-D-13-0153.1

c. Implementation of similarity criteria

The simulation of air dispersion in the wind tunnel must ensure the flow and diffusion similarity of the two systems [i.e., the wind tunnel (model) and the site (prototype: the building or structure in real world)]. The flow of the model and the prototype must meet the similarities of geometric, kinematic, dynamic, and boundary condition under neutral conditions. The dispersion characteristics of the plume will become similar as long as the flow similarity metrics listed by Guo et al. (2010) are satisfied. The necessity of meeting the criterion for the plume rise and dispersion similarity to simulate the diffusion is discussed by Yao et al. (1997). Thus, the following conditions in the wind tunnel experiment must be met to ensure that the experimental results are consistent with the actual condition:

  • 1) Geometric similarity of the wind tunnel: based on wind tunnel test section size and scale of simulated landform. The model scale is 1:1500.
  • 2) Kinematic similarity: this means that for the neutral atmosphere the approaching flow is required to match the (i) similarity of mean velocity profiles, (ii) equivalence of turbulent intensity and similarity of turbulent intensity profiles [turbulence intensity i = , where , is the ratio of fluctuation standard deviation velocity and average velocity and is a relative index for measuring the strength of the turbulence; turbulence intensity will have a proportional relationship with diffusion of air pollutants], and (iii) similarity of turbulent spectra between the model and the prototype.

The normalized velocity profile measured at 10 m from the start of the test section is in good agreement with the power law (with an index of 0.18) obtained from observations on the Pengzhe NPP site. Figure 3a gives the velocity profile and the measured values of wind velocity in the test section. The distribution of longitudinal turbulent intensity iX = is also shown in Fig. 3b (definitions of all variables used in this paper can be found in the appendix). It can be seen from Fig. 3 that they are consistent with each other.

  • 3) Dynamic similarity: this requires (i) matching Reynolds numbers, (ii) equivalence of momentum flux ratio, and (iii) approximate equivalence of Froude number. The Reynolds number on the top of cooling tower model is made equal to 11 000, which is the critical Reynolds number, by adjusting the wind speed. Equivalence of momentum flux ratio and Froude number of the plume between model and prototype are obtained by adjusting the density and speed of the plume of the cooling tower model.
Fig. 3.
Fig. 3.

Dependence of (a) normalized velocity profiles and (b) longitudinal turbulent intensity on height z.

Citation: Journal of Applied Meteorology and Climatology 53, 2; 10.1175/JAMC-D-13-0153.1

The initial bent-over appearance or rise caused by the initial momentum of the plume from the cooling tower is important. Thus, the plume condition similarity requires maintenance of the momentum flux ratio of the plume from the model to that of the prototype. At the same time, maintaining the relationship for the density ratio , where = , is also required. Therefore, the following relation is used to determine the experimental parameters:
e1

where m represents the model and p represents the prototype.

Equality of the Froude number is also required for the dynamic similarity of the plume at the exit of the cooling tower, that is,
e2

To satisfy the equality of the momentum flux ratio and the requirements for the density ratio (less than 0.4), the emission density and velocity of the plume from the cooling tower in the wind tunnel are evaluated using Eqs. (1) and (2).

  • 4) Boundary condition similarity: the surface of the experimental model must have the appropriate roughness. The boundary and reinforced wall roughness must also be similar, enabling the rough aerodynamic flow on the surface of the model. Basically, the flow must be turbulent, the sidewall must meet the following condition: μ* × z0/ν > 2.5, and the Reynolds number must be similar to that of the actual situation.

A thin serrated metal mesh of diameter of approximately 1–2 mm is installed in the cooling tower 10–20 mm away from the exit to ensure fully turbulent exhaust stream. Table 1 lists the main experimental parameters, which are calculated based on the above principles.

Table 1.

Simulated parameters of the cooling tower.

Table 1.

d. Measurement method

To quantitatively study the effect of the disturbance of cooling tower on flow, velocity measurements are made with a Dantec Dynamics constant temperature hot-wire anemometer. The hot-wire probes used in the X-array configuration are made of a platinum-coated tungsten wire of 5-μm diameter and 1.25-mm length. The tracer measurement system is adopted to measure the concentration distribution and to carry out a quantitative investigation on the diffusion laws of the plume from the cooling tower. CO is used as the tracer gas. The measurement system includes a CO release unit, a sampling unit, and two infrared gas analyzers. One is used for macroanalysis (with the measuring range of 0%–10%) and the other is used for microanalysis (with the measuring range of 0–2000 ppm).

3. Definitions of the visible plume region of the cooling tower

The plume rise from a cooling tower and the length of the visible plume regions are of interest from an environmental impact point of view. The length of the visible plume region from a cooling tower usually extends up to several hundred meters. The visible plume region and the plume rise from a cooling tower are mostly estimated on the basis of the relationship between the ambient liquid water content and specific humidity of the plume.

The process of mixing a plume with ambient air and subsequent visible plume formation due to condensation can be represented by straight line arrow, as shown in Fig. 4. The plume is visible when the specific humidity of plume is greater than the saturation specific humidity at the same temperature, that is, the plume is in a supersaturated state. Studies by Hanna et al. (1982) showed that 20% of the initial latent heat is transformed to sensible heat and then released in the continued heat exchange between the plume and the air.

Fig. 4.
Fig. 4.

Psychrometric chart. The curved line is the variation of saturation specific humidity with temperature.

Citation: Journal of Applied Meteorology and Climatology 53, 2; 10.1175/JAMC-D-13-0153.1

The visible region of a cooling tower plume cannot be directly measured in the wind tunnel experiment because the humidity from the cooling tower is modeled using the tracer gas. The present paper adopts the formula proposed by Michioka et al. (2007) to estimate the visible plume region in the wind tunnel experiment. The specific humidity q at the measuring point is calculated using the dilution rate Dr, the concentration at the measuring point C, and the emission concentration from the cooling tower Cc:
e3
e4
e5

At the measuring point, the visible plume region appears when q > qs. However, the visible plume region disappears when q < qs. The necessary input data such as temperature, humidity, and pressure are not measured in the wind tunnel experiment, but they are measured in the actual atmospheric environment instead. The saturation specific humidity at the measuring point may be estimated by the temperature and the saturation vapor pressure. The conversion rate of heat is assumed to be equal to the diffusion rate of gas. Therefore, the change in the temperature may be estimated according to the changes in concentration. Figure 5 shows the length, extent, and rise of a visible plume from the cooling tower, as defined in the present work.

Fig. 5.
Fig. 5.

Definitions of length, extent, and rise of visible plume from the cooling tower.

Citation: Journal of Applied Meteorology and Climatology 53, 2; 10.1175/JAMC-D-13-0153.1

4. Impacts of the cooling tower on the flow

Figure 6 shows the changes of normalized velocity (Fig. 6a) and longitudinal turbulent intensity (Fig. 6b) with height z measured at five different locations: the first one upwind (x = −3.0H, where H refers to the cooling tower height), the second one on top of the cooling tower (x = 0), and remaining three downwind (x = 3.0H, 5.0H, and 15.0H). All the locations are under or over the plume centerline (y = 0).

Fig. 6.
Fig. 6.

The changes of (a) normalized velocity and (b) longitudinal turbulent intensity measured at different locations.

Citation: Journal of Applied Meteorology and Climatology 53, 2; 10.1175/JAMC-D-13-0153.1

In the downwind direction from the top of cooling tower, the wind velocity in the near-wake region (including the backflow region) significantly decreases, whereas the turbulent intensity significantly increases. In the downwind direction of the cooling tower, the velocity reaches its minimum at a distance of 3.0H in the downwind direction from the top, where the wind speed is about 30% of that of the corresponding free flow. Also, at the same distance the turbulence intensity reaches its maximum value of approximately 0.5. The region with the higher turbulent intensity mainly appears near the backflow region. Farther downwind, the turbulence intensity gradually decreases and its vertical distribution approaches the free-flow condition. Based on the effect of cooling tower on velocities and turbulence intensities measured at different downwind distances, it can be determined that the height and length of the wake region are 1.5H and 15H, respectively.

5. The visible plume region and the rise in the height of the plume from the cooling tower

a. Visible plume region from the cooling tower

The present work uses the experimental data obtained using the Électricité de France (EDF) wind tunnel to validate the simulation result by Policastro and Wastag (1981). Their study was aimed at (i) a better understanding of the physics of cooling tower plume dispersion through basic parametric tests and (ii) providing experimental data for calibration and verification of the EDF cooling tower plume models. The EDF laboratory data have special advantages in that the ranges in physical parameters modeled by EDF were precisely those of cooling tower effluents. Laboratory studies available in the United States for single-source vertical jets do not have similar nondimensional parameters (densimetric Froude number and velocity ratio). As a result, the effects of downwash from the tower structure were treated. Also, the EDF laboratory studies included tests that involved multiple tower configurations.

Among the tests carried out are measurements on plumes from towers 1, 2, and 4, which are of equal size. The regime of interest for cooling tower plumes is 0.5 < k < 3 and Fr ~ 0.8. Here Fr is the initial densimetric Froude number of the tower effluent and k is the ratio of wind speed at tower height to the tower exit velocity. In the present work the value of k used is 1.4 and the Froude number is 0.89. Hence, these results are compared with the EDF wind tunnel experiment data for k = 1.5. Figure 7 shows the comparison of the visible plume region, in terms of normalized dimensions, between the current measurements and those from the EDF test.

Fig. 7.
Fig. 7.

Comparison of the results of present wind tunnel data and EDF data for the visible plume region; D is the cooling tower exit diameter.

Citation: Journal of Applied Meteorology and Climatology 53, 2; 10.1175/JAMC-D-13-0153.1

Figure 7 shows that the results of the visible region of the cooling tower plume in the present wind tunnel experiment agree with those of the EDF wind tunnel experiment. In both cases the maximum length of the visible plume region can reach 29D (D refers to cooling tower exit diameter) or more in the downwind direction of cooling tower. The maximum diameter of the visible plume region is about 3D.

Overcamp and Ku (1986) and Hoult and Weil (1972) verified the impacts of the variation of the k and Fr values on the path of the plume through a series of experiments. Their results showed that the relationship between the plume and the wake of the cooling tower varies with k. The relationship between the plume and the wake of the cooling tower becomes quite apparent when the k is greater than 1.0. The influence of the wake of the cooling tower on the plume is more for greater values of k. Moreover, the initial plume rise is higher when the wind velocity is less than 5 m s−1. The height of the plume is higher than that of the wake of the cooling tower. The visible plume region becomes smaller with an increase in wind velocity.

b. Visible plume rise from the cooling tower

Figure 8 shows the comparison of the plume rise height obtained in the present study with that calculated using the Briggs formula for buoyant plume rise (ΔH = 1.6F01/3x2/3/u, where x refers to downwind distance from the center of the cooling tower). Both the results show qualitatively the same behavior, that is, the plume rise height increases with distance for the length considered. The comparison is very good for 50 < x < 200 m. However, the difference between the two results gradually increases with the increasing distance. The measured plume rise from the cooling tower in the wind tunnel experiment is 430 m; the maximum length of the visible plume region appears at the distance of 3000 m in the downwind direction of the cooling tower.

Fig. 8.
Fig. 8.

The rise of the cooling tower plume with downwind distance: comparison of the wind tunnel data with Briggs's numerical results.

Citation: Journal of Applied Meteorology and Climatology 53, 2; 10.1175/JAMC-D-13-0153.1

The formula proposed by Briggs is based on the assumption that the heat flux remains unchanged in the process of plume transport and diffusion, an assumption that does not account for evaporative cooling of the water droplets from the visible cloud. This could be the reason for larger deviations between the two results of the plume rise height away from the cooling tower.

6. Conclusions

The simulation method of a plume from a cooling tower proposed in the present paper could model the region of visible plume and its rise from a natural draft cooling tower. The present results validate the EDF wind tunnel experimental data according to Policastro and Wastag (1981).

The present results on the flow field around a cooling tower show that the existence of a cooling tower causes flow field distortion. This distortion gradually declines with the distance from the cooling tower. The minimum velocity in the downwind direction of a cooling tower occurs at about 3H, where the wind speed is about 30% of that of the corresponding free velocity. Also, the turbulent kinetic energy reaches its peak with the turbulent intensity increased to around 0.5 at the same location. The height and length of the wake region are 1.5H and 15H, respectively.

The maximum length of the visible plume region can reach about 29D in the downwind direction of the cooling tower, and the maximum diameter of the visible plume region is about 3D. The measured plume rise from the cooling tower in the wind tunnel experiment corresponds to 430 m in the real world, and the maximum length of the visible plume region appears at a corresponding distance of 3000 m in the downwind direction from the cooling tower. The results show that the visible plume region is nearly in agreement with the EDF wind tunnel experimental data. Hence, the present wind tunnel method seems to predict the visible region of the cooling tower plume.

Under the actual situation of the inland nuclear power plant of China, the height of the cooling tower is about 200 m, and the height of the chimney is approximately 75 m, so the height of the chimney is far below the cooling tower. Therefore, the cooling tower has significant impacts on the radionuclide release within a few hundred meters. When the water vapor rises into the air at a low wind velocity, it may cause some changes in local microclimate and increase the formation of fog. Since no previous research regarding this phenomenon has been performed, further study is needed.

Acknowledgments

This work was supported by National Natural Science Fund of China (Grant 11175161) and Doctor Fund of Taiyuan University of Science and Technology (Grant 20122008).

APPENDIX

Symbol Descriptions

i Turbulent intensity

iX Longitudinal turbulent intensity

 Fluctuation standard deviation velocity (m s−1)

 Average velocity (m s−1)

Fr Froude number

ΔH Visible plume rise height (m)

H Cooling tower height (m)

x Downwind distance from cooling tower (m)

D Cooling tower exit diameter (m)

L Length of visible plume from cooling tower (m)

qL0 The initial specific humidity of liquid water in the plume (g g−1)

qp0 Specific humidity of plume from the exit of cooling tower (g g−1)

qs Saturation specific humidity in the ambient air (g g−1)

qe Specific humidity in the ambient air (g g−1)

q Specific humidity measured at a point in wind tunnel (g g−1)

u Wind velocity (m s−1)

W Plume emission rate (m s−1)

F0 Initial sensible heat flux of plume (m4 s−3)

Ps Saturation vapor pressure (Pa)

P Aqueous vapor pressure (Pa)

g Acceleration due to gravity (m s−2)

Δρ Difference between air density and density of plume emission, ρaρs (kg m−3)

ρs Density of plume emission (kg m−3)

ρa Air density (kg m−3)

μ* Surface friction velocity (m s−1)

z0 Surface roughness length (m)

ν Coefficient of kinematic viscosity of air (m2 s−1)

k Ratio of wind speed at tower height to the tower exit velocity, k = u/W

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    • Search Google Scholar
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    • Search Google Scholar
    • Export Citation
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    • Search Google Scholar
    • Export Citation
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    • Search Google Scholar
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