Remote Measurement of Heat Flux from Power Plant Cooling Lakes

Alfred J. Garrett Savannah River National Laboratory, Aiken, South Carolina

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Robert J. Kurzeja Savannah River National Laboratory, Aiken, South Carolina

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Eliel Villa-Aleman Savannah River National Laboratory, Aiken, South Carolina

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James S. Bollinger Savannah River National Laboratory, Aiken, South Carolina

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Malcolm M. Pendergast Savannah River National Laboratory, Aiken, South Carolina

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Abstract

Laboratory experiments have demonstrated a correlation between the rate of heat loss q″ from an experimental fluid to the air above and the standard deviation σ of the thermal variability in images of the fluid surface. These experimental results imply that q″ can be derived directly from thermal imagery by computing σ. This paper analyses thermal imagery collected over two power plant cooling lakes to determine if the same relationship exists. Turbulent boundary layer theory predicts a linear relationship between q″ and σ when both forced (wind driven) and free (buoyancy driven) convection are present. Datasets derived from ground- and helicopter-based imagery collections had correlation coefficients between σ and q″ of 0.45 and 0.76, respectively. Values of q″ computed from a function of σ and friction velocity u* derived from turbulent boundary layer theory had higher correlations with measured values of q″ (0.84 and 0.89). This research may be applicable to the problem of calculating losses of heat from the ocean to the atmosphere during high-latitude cold-air outbreaks because it does not require the information typically needed to compute sensible, evaporative, and thermal radiation energy losses to the atmosphere.

Retired.

Corresponding author address: Alfred J. Garrett, Savannah River National Laboratory, Office B-108, Bldg. 735-A, Aiken, SC 29808. E-mail: alfred.garrett@srnl.doe.gov

Abstract

Laboratory experiments have demonstrated a correlation between the rate of heat loss q″ from an experimental fluid to the air above and the standard deviation σ of the thermal variability in images of the fluid surface. These experimental results imply that q″ can be derived directly from thermal imagery by computing σ. This paper analyses thermal imagery collected over two power plant cooling lakes to determine if the same relationship exists. Turbulent boundary layer theory predicts a linear relationship between q″ and σ when both forced (wind driven) and free (buoyancy driven) convection are present. Datasets derived from ground- and helicopter-based imagery collections had correlation coefficients between σ and q″ of 0.45 and 0.76, respectively. Values of q″ computed from a function of σ and friction velocity u* derived from turbulent boundary layer theory had higher correlations with measured values of q″ (0.84 and 0.89). This research may be applicable to the problem of calculating losses of heat from the ocean to the atmosphere during high-latitude cold-air outbreaks because it does not require the information typically needed to compute sensible, evaporative, and thermal radiation energy losses to the atmosphere.

Retired.

Corresponding author address: Alfred J. Garrett, Savannah River National Laboratory, Office B-108, Bldg. 735-A, Aiken, SC 29808. E-mail: alfred.garrett@srnl.doe.gov
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