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www.drink-water-eng-sci-discuss.net/1/117/2008/
doi:10.5194/dwesd-1-117-2008
© Author(s) 2008. This work is distributed
under the Creative Commons Attribution 3.0 License.
Verification of filter efficiency of horizontal roughing filter by Weglin's design criteria and Artificial Neural Network
1KMW&SA, Kolkata, India
2School of Water Resources Engineering, Jadavpur University, Kolkata, India
3B. P. Poddar Institute of Management and Technology, Kolkata, India
Abstract. The general objective of this study is to estimate the performance of the Horizontal Roughing Filter(HRF) by using Weglin's design criteria based on 1/3–2/3 filter theory. The motive is to reduce the Slow Sand load in the raw water by using HRF as the pretreatment unit, but the main objective is to verify the Weglin's design criteria for HRF with respect to raw water condition. A model was also built with the help of neural network which tries to predict the filter efficiency of the HRF. Three results achieved from the three different models were compared to find whether the experimental HRF output conforms to the other two models. According to the results the results from experimental setup is coherent with the neural model but incoherent with the results from Weglin's formula. As neural models are known to learn a problem with utmost efficiency, the model verification result was taken as positive.
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Notice on Discussion StatusCitation: Mukhopadhay, B., Majumder, M., Nath Barman, R., Kumar Roy, P., and Mazumder, A.: Verification of filter efficiency of horizontal roughing filter by Weglin's design criteria and Artificial Neural Network, Drink. Water Eng. Sci. Discuss., 1, 117-133, doi:10.5194/dwesd-1-117-2008, 2008. Bibtex EndNote Reference Manager XML
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