Flow Pattern Study and Pressure Drop Prediction of Two-Phase Boiling Process in Different Surface Wettability Microchannel

Author:

Zhang Yuqi1ORCID,Wu Haoxian1,Zhang Ling23,Yang Yunbo1,Niu Xiangdong23,Zeng Zerong23,Shu Bifen1

Affiliation:

1. School of Physics, Sun Yat-sen University, Guangzhou 510006, China

2. Shuifa Singyes Energy (Zhuhai) Co., Ltd., Zhuhai 519000, China

3. Zhuhai CABEE Singyes Green Building Design & Research Institute Co., Ltd., Zhuhai 519000, China

Abstract

An experimental study of two-phase flow pressure drop using R-134a is conducted on three types of different surface wettability microchannels with superhydrophilic (contact angle of 0°), hydrophilic (contact angle of 43°) and common (contact angle of 70°, unmodified) surfaces, all with a hydraulic diameter of 0.805 mm. Experiments were conducted using a mass flux of 713–1629 kg/m2s and a heat flux of 7.0–35.1 kW/m2. Firstly, the bubble behavior during the two-phase boiling process in the superhydrophilic and common surface microchannel is studied. Through a large number of flow pattern diagrams under different working conditions, it is found that the bubble behavior shows different degrees of order in microchannels with different surface wettability. The experimental results show that the hydrophilic surface modification of microchannel is an effective method to enhance heat transfer and reduce friction pressure drop. Through the data analysis of friction pressure drop and C parameter, it is found that the three most important parameters affecting the two-phase friction pressure drop are mass flux, vapor quality, and surface wettability. Based on flow patterns and pressure drop characteristics obtained from the experiments, a new parameter, named flow order degree, is proposed to account for the overall effects of mass flux, vapor quality, and surface wettability on two-phase frictional pressure drop in microchannels, and a newly developed correlation based on the separated flow model is presented. In the superhydrophilic microchannel, the mean absolute error of the new correlation is 19.8%, which is considerably less than the error of the previous models.

Funder

Natural Science Foundation of Guangdong province of China

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Mechanical Engineering,Control and Systems Engineering

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