Observation of Thermal Plumes from Submerged Discharges in the Great Lakes and Their Implications for Modeling and Monitoring

摘要

Measurements of thermal plumes from submerged discharges of power plant cooling waters into the Great Lakes provide the opportunity to view the mixing processes at prototype scales and to observe the effects of the ambient environment on those processes. Examples of thermal plume behavior in Great Lakes' ambient environments are presented to demonstrate the importance of measurements of the detailed structure of the ambient environment, as well as of the plumes, for interpretation of prototype data for modeling and monitoring purposes. The examples are drawn from studies by Argonne National Laboratory (ANL) at the Zion Nuclear PowerStation and the D. C. Cook Nuclear Plant on Lake Michigan and at the J. A. FitzPatrick Nuclear Power Plant on Lake Ontario. These studies included measurements of water temperatures from a moving boat which provide a quasi-synoptic view of the three-dimensional temperature structure of the thermal plume and ambient water environment. Additional measurements of water velocities, which are made with continuously recording, moored, and profiling current meters, and of wind provide data on the detailed structure of the ambient environment. The detailed structure of the ambient environment, in terms of current, current shear, variable winds, and temperature stratification, often influence greatly thermal plume behavior. Although predictive model techniques and monitoring objectives often ignore the detailed aspects of the ambient environment, useful interpretation of prototype data for model evaluation or calibration and monitoring purposes requires detailed measurement of the ambient environment. Examination of prototype thermal plume data indicates that, in several instances, attention to only the gross characteristics of the ambient environment can be misleading and could result in significant errors in model calibration and extrapolation of data bases gathered in monitoring observations. (ERA citation 03:055873)