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• W2079238979 abstract "Process control at older water reclamation plants (WRPs) can be challenging as operators work to balance higher energy costs and more stringent effluent limitations while managing fluctuating loads. To better understand WRP loading characteristics, we developed a classification system for the Metropolitan Water Reclamation District of Greater Chicago (MWRDGC) Calumet WRP by combining k-means cluster analysis with cross-tabulation analysis. Based on weather and influent composition characteristics, we identified 25 clusters; nine of those clusters are significant (99% confidence level) based on chi-square tests. Dry weather and middle temperature conditions after wet-weather days are common, and compared to cold-weather flows, warm-weather flows are more likely to have large precipitation events and more variation in influent quality. To explore how information about influent scenarios could inform process control and improve process efficiency, we also developed a process simulation model. The model indicates that aeration strategies for each of the nine scenarios could be modified to make it possible for the plant to operate more efficiently while still meeting effluent requirements. The approach described here can provide useful information on the frequency and duration of different types of loading, enabling WRP operators to move toward more flexible and efficient operations." @default.
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• W2079238979 date "2015-07-01" @default.
• W2079238979 modified "2023-10-03" @default.
• W2079238979 title "Defining Influent Scenarios: Application of Cluster Analysis to a Water Reclamation Plant" @default.
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• W2079238979 doi "https://doi.org/10.1061/(asce)ee.1943-7870.0000934" @default.
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