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- W1831843172 abstract "This chapter presents a case study that explores the development of a model for predicting temperatures in six distillation tower trays under varying operating conditions. The tray temperatures are important in that they determine the distillation tower's product quality. The input parameters used as inputs to the model include the feed rate, the feed temperature, the flow rates and chemical composition of the reflux streams, the purge flow rate, and the rate of steam flowing to the reboiler. To avoid biasing training by a large number of data points over periods of operations where conditions essentially remained unchanged, the data needed to be mined for identifying distinctly different operating conditions within this dataset before they are used to develop a model for predicting the tower tray temperatures. The outcomes predicted by the model are the temperatures in the six trays at different positions in the tower." @default.
- W1831843172 created "2016-06-24" @default.
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- W1831843172 date "2005-01-01" @default.
- W1831843172 modified "2023-09-27" @default.
- W1831843172 title "Predicting Distillation Tower Temperatures" @default.
- W1831843172 doi "https://doi.org/10.1016/b978-008044538-0/50073-2" @default.
- W1831843172 hasPublicationYear "2005" @default.
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