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Stephen A. Vigeant, CCM and Carl A. Mazzola, CCM Shaw Environmental & Infrastructure

An Analytical Screening Technique to Estimate the Effect of Cooling Ponds on Meteorological Measurements – A Case Study. Stephen A. Vigeant, CCM and Carl A. Mazzola, CCM Shaw Environmental & Infrastructure. PAMS Mini-Conference, Columbia, SC; April 3, 2009. Outline. Introduction

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Stephen A. Vigeant, CCM and Carl A. Mazzola, CCM Shaw Environmental & Infrastructure

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  1. An Analytical Screening Technique to Estimate the Effect of Cooling Ponds on Meteorological Measurements – A Case Study Stephen A. Vigeant, CCM and Carl A. Mazzola, CCM Shaw Environmental & Infrastructure PAMS Mini-Conference, Columbia, SC; April 3, 2009

  2. Outline • Introduction • Study Objective • Technical Approach • Sensible heat and moisture flux source terms • Atmospheric transport and diffusion • Results • Conclusions

  3. Introduction • Situation: Overseas nuclear power station meteorological monitoring program with 2 instrumented towers (58-meter; 10-meter) • Cooling system: Includes two 12 m x 12 m cooling ponds with elevated water temperatures • Ponds: Located 62 meters from 10-meter tower instrumentation • Issue: Nuclear regulatory agency concerned about possible effects of cooling ponds on 10-meter tower measurements

  4. Study Objective • Develop analytical technique to estimate potential impact of cooling ponds on 10-meter tower temperature and RH measurements • Source Terms: Estimate sensible heat and moisture fluxes from cooling ponds • Atmospheric Transport and Diffusion: Determine impacts of fluxes on 10-meter tower measurements using appropriate model • Use 1-year of onsite data to estimate source term and atmospheric transport and diffusion • Calculate temperature and moisture impacts to 10-meter tower instrumentation

  5. Technical Approach:Sensible Heat and Moisture Fluxes • Bulk aerodynamic formulae of Friehe and Schmitt (1976) selected to estimate sensible heat and moisture fluxes from cooling ponds • Fluxes primarily driven by • Water and air temperature differences • Wind speed above ponds

  6. Sensible Heat and Moisture Fluxes Wind Sensible Heat & Moisture Fluxes Ta Discharge Pond Ts

  7. Technical Approach:Sensible Heat and Moisture Fluxes Sensible Heat Flux Hs = rCpCHU(Ts – Ta) where: Hs = sensible heat flux (cal m-2 sec-1) r = air density (g m-3) Cp = heat capacity of air (cal g-1 °K-1) CH = sensible heat transfer coefficient (dimensionless) U = mean wind speed (m sec-1) at reference height (10 meters) Ts = mean water temperature (°K) Ta = mean air temperature at reference height (10 meters) (°K)

  8. Technical Approach:Sensible Heat and Moisture Fluxes Moisture Flux E = CeU(Qs – Qa) where: E = moisture flux (g m-2 sec-1) Ce = moisture transfer coefficient (dimensionless) U = mean wind speed (m sec-1) at reference height (10 meters) Qs = mean water vapor density (g/m3) near the water surface (assume saturation) Qa = mean water vapor density (g/m3) at reference height (10 meters)

  9. Technical Approach:Sensible Heat and Moisture Fluxes Water vapor densities (Qs and Qa) Qs and Qa = r[(RH x Ws) / (1 + RH x Ws)] where: r = air density (g m-3) Ws = saturation mixing ratio (dimensionless) RH = relative humidity (dimensionless) Qs (based on water temperature) Qa (based on air temperature)

  10. Technical Approach:Sensible Heat and Moisture Flux Source Terms • Calculate hourly sensible heat and moisture fluxes using one year of onsite measurements • Base sensible heat transfer coefficients (CH) on seasonal values obtained from site-specific study • Base moisture transfer coefficient (Ce) on Friehe & Schmitt • Use seasonal intake water temperature measurements • Assume pond temperature is 7°C higher • Assume flux homogeneity over entire pond surface • Multiply calculated fluxes (cal m-2 sec-1; g m-2 sec-1) by pond surface area • Obtain sensible heat and moisture “source terms” (cal sec-1; g sec-1)

  11. Technical Approach:Atmospheric Transport and Diffusion • Determine transport and diffusion of sensible heat and moisture “source terms” • Calculate normalized concentrations (C/Qs) at 10-meter tower located 62 meters from cooling ponds • Use NRC ARCON96 code due to close proximity of source and “receptor” • Horizontal and vertical diffusion coefficients adjusted for plume meander and aerodynamic building wake • Empirical adjustments based on many wind tunnel and atmospheric tracer studies • NUREG/CR-6331 Revision 1 • Use hourly onsite data from 10-m tower: ARCON96 input

  12. Technical Approach:Atmospheric Transport and Diffusion ARCON96 Code Description • Straight-line Eulerian Gaussian plume • Ground-level, vent, and elevated releases • Incorporates low wind speed plume meander • Incorporates aerodynamic building wake effects • Valid at source-receptor distances as close as 10 meters • Recommended by NRC for use in control room habitability analyses in Regulatory Guide 1.194

  13. Technical Approach:Atmospheric Transport and Diffusion ARCON96 Code Input Options • Area source (virtual point) option used for cooling ponds • Sector averaging constant (4.3) • Wind direction sector width (90 degrees azimuth) • Surface roughness length (0.2 m) • One year of hourly onsite meteorological data

  14. Technical Approach:Sensible Heat and Moisture Concentrations • Multiply sensible heat (cal sec-1) and moisture (g sec-1) fluxes by calculated ARCON96 C/Q values (sec m-3) • Obtain hourly values of sensible heat (XH) (cal m-3) and moisture concentration (Xw) (g m-3) at 10-m tower instruments XH = Hs (C/Q) Sensible Heat Concentration XW = E (C/Q) Water Vapor Concentration

  15. Technical Approach:Pond Sensible Heat and Moisture Impact Calculations Calculate increase in temperature (DTa) at 10-meter tower DTa = XH/Cpr Calculate increase in RH (DRH) at 10-meter tower DRH = 100 x [XW (g m-3) / rW (g m-3)]

  16. Results • Temperature Impact • Largest hourly temperature impact: + 0.2°C • Increase between 0.10°C - 0.19°C (0.3% of time) • Increase between 0.01°C - 0.09°C (24% of time) • Increase of < 0.01°C (14% of time) • No impact when wind direction outside of 90-degree azimuth ARCON96 window (62% of time) • RH Impact • Largest hourly RH impact: + 0.7% • ANSI/ANS-3.11 (2005) and NRC Regulatory Guide 1.23 Revision 1 accuracy requirements • Air temperature ± 0.5 °C • RH ± 4%

  17. Conclusions • Temperature and moisture increases due to presence of discharge ponds at 10-meter tower not significant • Slight increases • Much smaller than ANSI/ANS-3.11 accuracy standard for each parameter • Have no meaningful effect on meteorological data used to evaluate environmental impacts of nuclear power plant • No effect of discharge pond on wind speed and wind direction is expected

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