Degree Name

Master of Arts (MA)

Semester of Degree Completion

1977

Thesis Director

Suhrit K. Dey

Abstract

Many models have been developed for or applied to the prediction of mechanical draft cooling tower plumes. However, due to a serious lack of data up to this date, little has been done to verify the predictive capability of these mathematical models. This thesis attempts to rectify this situation somewhat by undertaking a thorough investigation of the plume theories of G. A. Briggs and S. R. Hanna. A study of their theoretical foundations and development, practical formulations, and ability to predict the height and length of the visible portion of mechanical-draft cooling tower plumes is undertaken. Detailed derivations of their predictive equations are presented along with an analysis of the key assumptions needed for their development. Methods of evaluating parameters and techniques by which the models may be extended are examined. Also, the model of Eagles and Kohlenstein is presented as an example of the application of Briggs' and Hanna's plume theories.

Two collections of mechanical-draft cooling tower data (gathered at the Benning Road, Washington, D. C., and Purdue University, Indiana, power plants) are outlined and their utility for model verification discussed. They are used to test the models of Briggs, Hanna, and Eagles-Kohlenstein, with the following results: Briggs' simplest model, though not designed for visible plume predictions, does reasonably well; Hanna's plume predictions are well correlated with the observed plume features, but they tend to consistently over- or under-predict plume height and length; Eagles-Kohlenstein's model, which was calibrated with one of the data sets, tends to give predictions similar to the simpler Hanna model. It is concluded that, although further studies should be made, these models can be expected to give factor of two to three predictions, if properly utilized, of the maximum height and length of mechanical-draft cooling tower plumes which extend a sufficient distance from their sources.

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