Gas-Liquid Two-Phase Flow Pattern Identification of a Centrifugal Pump Based on SMOTE and Artificial Neural Network.

ABSTRACT: The accurate identification of the gas-liquid two-phase flow pattern within the impeller of a centrifugal pump is critical to develop a reliable model for predicting the gas-liquid two-phase performance of the centrifugal pump. The influences of the inlet gas volume fraction, the liquid phase flow rate and the pump rotational speed on the flow characteristics of the centrifugal pump were investigated experimentally. Four typical flow patterns in the impeller of the centrifugal pump, i.e., the bubble flow, the agglomerated bubble flow, the gas pocket flow and the segregated flow, were obtained, and the corresponding flow pattern maps were drawn. After oversampling based on the SMOTE algorithm, a four-layer artificial neural network model with two hidden layers was constructed. By selecting

SUBMITTER: He D 

PROVIDER: S-EPMC8778694 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature