Assessing the Efficiency of Wastewater Evaporation through Fuzzy Logic Models

## Fangtian Li – Evaluation of the Wastewater Evaporation Using Fuzzy Logic Models

Welcome to my YouTube video on the evaluation of wastewater evaporation using fuzzy logic models. As a graduate assistant in the Department of Chemical Engineering at the University of North Dakota, I have conducted extensive research on the feasibility of using wastewater evaporation as a treatment method to reduce the amount of wastewater disposed.

Wastewater desalination is a crucial part of water resource management, and mechanical vapor recompression is an energy-efficient technique that can be used for this purpose. In this study, I explored the conditions necessary for the successful application of this technique, considering parameters such as salinity, organic content, pH, chemical oxygen demand, and electrical conductivity.

By analyzing 57 water samples, I identified 41 samples suitable for direct mechanical evaporation, while 16 samples did not meet the criteria. I have presented some intriguing results, such as instances where certain parameters, such as electrical conductivity and boiling points, affected the suitability of wastewater for the evaporation process.

To simplify the determination of wastewater suitability, I developed a final model based on fuzzy logic. This model allowed for the easy classification of samples, considering key parameters and their respective levels. Utilizing a confusion matrix, I evaluated the model’s performance, achieving an impressive 81.2% accuracy.

In conclusion, this study establishes a clear relationship between wastewater properties and its suitability for evaporation. The fuzzy logic model developed here effectively evaluates and classifies wastewater with near-perfect agreement. Join me in this enlightening video as I discuss the nuances of wastewater evaporation using fuzzy logic models.

(Source: [University of North Dakota](

Fangtian Li – Evaluation of the Wastewater Evaporation Using Fuzzy Logic Models

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