Identification of Flow Patterns in Upward Inclined Two-Phase Flows by Artificial Neural Network

Lin, Z. and Liu, X. (2019) Identification of Flow Patterns in Upward Inclined Two-Phase Flows by Artificial Neural Network. In: 11th International Conference on Applied Energy (ICAE2019), Västerås, Sweden, 12-15 Aug 2019, 0626.

Full text not currently available from Enlighten.

Publisher's URL: http://www.energy-proceedings.org/identification-of-flow-patterns-in-upward-inclined-two-phase-flows-by-artificial-neural-network/

Abstract

This paper presented a methodology of artificial neural network (ANN) for the prediction of flow patterns in two-phase air-water flow along upward inclined pipes. In the built ANN model, superficial velocity of air, superficial velocity of water, and inclined angle were set as inputs while the quantified flow patterns were defined as the output. In total, 1952 experimental data points that were reported in the literature were trained and tested by the designed network structure. The predicting accuracies of stratified smooth, stratified wavy, annular, intermittent, bubble flow are all above 90%, with the exception of dispersed bubble flow.

Item Type:Conference Proceedings
Additional Information:Oral presentation.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Liu, Dr Xiaolei
Authors: Lin, Z., and Liu, X.
College/School:College of Science and Engineering > School of Engineering > Systems Power and Energy
Related URLs:

University Staff: Request a correction | Enlighten Editors: Update this record