Open AccessRegime identification of slurry transport in pipelines: A novel modelling approach using ANN & differential evolution
Author(s) -
Sandip Kumar Lahiri,
Kartik Chandra Ghanta
Publication year - 2010
Publication title -
chemical industry and chemical engineering quarterly
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.189
H-Index - 26
eISSN - 2217-7434
pISSN - 1451-9372
DOI - 10.2298/ciceq091030034l
Subject(s) - slurry , pipeline transport , artificial neural network , pressure drop , pipeline (software) , differential evolution , suspension (topology) , range (aeronautics) , mechanics , computer science , biological system , engineering , mathematics , algorithm , mechanical engineering , artificial intelligence , physics , environmental engineering , homotopy , pure mathematics , biology , aerospace engineering
Four distinct regimes were found existent (namely sliding bed, saltation, heterogeneous suspension and homogeneous suspension) in slurry flow in pipeline depending upon the average velocity of flow. In the literature, few numbers of correlations has been proposed for identification of these regimes in slurry pipelines. Regime identification is important for slurry pipeline design as they are the prerequisite to apply different pressure drop correlation in different regime. However, available correlations fail to predict the regime over a wide range of conditions. Based on a databank of around 800 measurements collected from the open literature, a method has been proposed to identify the regime using artificial neural network (ANN) modeling. The method incorporates hybrid artificial neural network and differential evolution technique (ANN - DE) for efficient tuning of ANN Meta parameters. Statistical analysis showed that the proposed method has an average misclassification error of 0.03%. A comparison with selected correlations in the literature showed that the developed ANN - DE method noticeably improved prediction of regime over a wide range of operating conditions, physical properties, and pipe diameters. .