Investigation Of Enhancing Flow Boiling Heat Transfer And Bubble Characteristics And Flow Pattern Image Intelligent Identification In Rectangular Mini-channel Under Ultrasonic Wave

In the heat transfer arena,heat dissipation is a problem that needs to be solved in energy power,biochemical industry,military industry,nuclear energy and many other industries.Using mini-channels is an important method to solve the problem of high heat flux.Due to the limitation of mini-channels heat transfer system structure and the requirement of high heat flux,single traditional enhanced heat transfer technology can't fully meet current heat transfer requirements of all equipment,so it is necessary to apply active enhanced technology to mini-channels heat exchanger.Because heat transfer characteristics are closely related to flow pattern,this paper uses video image detection technology and artificial intelligence technology to study flow boiling enhancement heat transfer characteristics of rectangular mini-channels under the action of ultrasound,and explores heat transfer mechanism of mini-channels under the action of ultrasound.The main research contents are as follows:(1)The flow boiling characteristics of R141 b in rectangular mini-channels under the action of ultrasound are studied.The high-speed camera and video technology are used for visualization.The bubble growth behavior characteristics during flow boiling under the action of ultrasound are analyzed,and the bubble motion mechanism is analyzed from the mechanical point of view.It is found that small bubbles will be produced under the action of ultrasound,which increases the chance of bubble merging and makes bubbles grow more easily into confined bubbles.In addition,ultrasonic wave can also cause the movement behavior of bubbles to change.In the process of bubble growth,bubbles oscillate between heated walls and jump upward,and the movement speed are divided into two stages: low-speed and high-speed long.(2)The process of continuous growth of single bubble into elongated bubble under the action of ultrasonic is studied in detail.The ratio of bubble diameter to channel width and the ratio of bubble width to length are calculated by using image measurement technology.The growth and heat transfer mechanism of confined bubble and elongated bubble during flow boiling under the action of ultrasonic are analyzed.It is found that the bubble growth process can be divided into three stages: free growth,restricted growth and elongated growth.When bubbles grow freely,the equivalent diameter of bubbles changes with time to meet the power-law model.During flow boiling of mini-channels,when the bubble enters into the confined growth,the curve of the top gas-liquid interface gradually decreases towards the wall,resulting in the instability of two-phase flow in the mini-channels.(3)In view of great influence of gas-liquid two-phase flow pattern on heat transfer and pressure drop,this paper introduces machine learning method to realize two-phase flow pattern recognition.According to flow pattern image of high-speed camera in the experiment,the edge features of flow pattern image are extracted as learning samples to identify the gas-liquid two-phase flow pattern of mini-channels flow boiling.Using intelligent identification to automatically analyze the restricted bubbles and restricted elongated bubbles under the action of ultrasound,including calculating the area,spacing,number of restricted bubbles and the gap between bubbles and heating wall.It is found that the ultrasonic wave makes the downstream confined bubbles of adjacent bubbles easy to form elongated bubbles,and the upstream bubble size suddenly decreases.The numerical simulation of the adjacent elongated bubbles shows that the temperature field around the elongated bubbles is quite different,and a larger temperature gradient is formed in the channel to redistribute the temperature field,which is helpful to improve heat transfer performance.(4)The pressure drops characteristics of flow boiling in mini-channels under the action of ultrasound were studied.A multi-scale convolution depth learning model is proposed to predict two-phase pressure drop of mini-channel flow boiling under the action of ultrasound.Combined with the experimental data,it is compared with five traditional mathematical correlations and traditional convolution neural prediction models.The MAE and NRMSE are 5.6% and 38.11%,respectively,which show that the prediction results of multi-scale convolution neural network are reliable.Ultrasound can change the bubble dynamics of mini-channels,which has a certain effect on the total pressure drop and two-phase friction pressure drop.The ultrasonic wave causes the bubble to compress and expand,and then causes the pressure drop fluctuation.