Study on Measure Approach of Void Fraction in Narrow Channel Based on Fully Convolutional Neural Network

Wenjun Chu,Liqiang Pan,Xingtuan Yang,Yang Liu,Hongye Zhu

doi:10.3389/fenrg.2021.636813

Abstract

Void fraction is one of the key parameters for gas-liquid study and detection of nuclear power system state. Based on fully convolutional neural network (FCN) and high-speed photography, an indirect void fraction measure approach for flow boiling condition in narrow channels is developed in this paper. Deep learning technique is applied to extract image features and can better realize the identification of gas and liquid phase in channels of complicated flow pattern and high void fraction, and can obtain the instantaneous value of void fraction for analyzing and monitoring. This paper verified the FCN method with visual boiling experiment data. Compared with the time-averaged experimental results calculated by the energy conservation method and the empirical formula, the relative deviations are within 11%, which verifies the reliability of this method. Moreover, the recognition results show that the FCN method has promising improvement in the scope of application compared with the traditional morphological method, and meanwhile saves the design cost. In the future, it can be applied to void fraction measurement and flow state monitoring of narrow channels under complex working conditions.

Highlights

Gas-liquid two-phase flow reserves value for the research in fields of nuclear energy, petrochemical industry, erospace and various industrial applications (Triplett et al, 1999)
In order to solve these problems, this paper proposes a new image segmentation algorithm of fully convolutional neural network (FCN) method based on deep learning technology
The data set used in the experiment in this paper comes from the images collected by the visual narrow channel flow boiling experiment system of Tsinghua University

Summary

Introduction

Gas-liquid two-phase flow reserves value for the research in fields of nuclear energy, petrochemical industry, erospace and various industrial applications (Triplett et al, 1999). In the two-phase flow study and engineering application, the cross sectional void fraction (or frequently abbreviated to void fraction) which functions as one of the key parameters, has important significance for determining the flow pattern, calculating the two-phase pressure drop and analyzing heat transfer characteristics (Winkler et al, 2012). Some common methods in experiments include quick-closing valves (Srisomba et al, 2014), X-ray/γ-ray absorption (Zhao Y et al, 2016; Jahangir et al, 2019), differential pressure (Jia et al, 2015) and capacitive method (Jaworek et al, 2014). The narrow rectangular channel is an important structure of these systems. The flow boiling phenomenon tends to be more complicated in narrow channels than in normal pipelines, and direct

Methods

Results

Conclusion