AWWA WQTC60792

Multivariate polynomial regression analysis was used to develop mathematical models to predict filter head loss, effluent turbidity, and effluent for 2- to 5-micron (µm) particle counts based on influent waterquality data and filter operating data. The models were developed using full-scale operating data, which is typically collected at water treatment plants, supplemented with online instrumentation for themeasurement of particle counts and turbidity. The resulting models can be used as indicators to assess treatment plant performance. The models are capable of evaluating the filter system's response to changesin filtration rate, influent turbidity, and total particle counts. The models indicate that although providinginfluent water low in turbidity and particle counts to a filter will reduce the rate of head loss development,it can adversely affect filter water quality in terms of ripening times and effluent particle counts. Includes 10 references, tables, figures.

Product Details

Edition:

Vol. - No.

Published:

11/15/2004

Number of Pages:

17

File Size:

1 file , 790 KB