Study of water condensation over cooled surfaces of humid non-condensable gas streams

Author:

Pozzobon João Carlos1,Mantelli Marcia Barbosa Henriques2,Milanese Fernando Henrique2

Affiliation:

1. Federal Institute of Santa Catarina

2. Federal University of Santa Catarina

Abstract

Abstract

The water consumption rate and scarcity of water sources also suggest the high importance of proper water management, especially in the industrial context. Some of the many approaches that could be taken to help conserve industrial water resources include condensing steam emitted in cooling towers. This work aims to evaluate the performance of the finned tube heat exchanger for water steam recuperation in various industries. To accomplish this goal, three different types of evaluation methods were used for the current heat exchanger under investigation. First, steady-state CFX simulations were made using a core section of the heat exchanger. The second approach was another CFX simulation different from the first one where a new geometry which comprises of parallel flat plates approximating the heat exchanger was used. Last of all, with the help of the third method, a semi-theoretical model, which was established and validated before to describe the required thermophysical processes, was employed. The findings indicate that the heat exchanger can successfully recover up to 24% of water steam, or more so depending on the temperature difference of the wall thickness and the steam/air mixture to about 14.5 K, the outcome is far less favorable, where it is assumed that the temperature difference is only 4.5 K the effectiveness of the recovery is still at about 2 percent. More importantly, the theoretical consideration also shows that, by using a rectangular channel made up of parallel flat plates, it is possible to model the complex geometry of a finned tube heat exchanger and obtain results that are within 2% of the benchmark. Moreover, the semi-theoretical model does not yield less accurate but more conservative coefficients of determination. These coefficients of determination represent the model's ability to explain the variability in the data, with higher values indicating a better fit.

Publisher

Springer Science and Business Media LLC

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