Abstract
In the paper, a self-organizing map combined with the recurrence quantification analysis was used to identify flow boiling patterns in a circular horizontal minichannel with an inner diameter of 1 mm. The dynamics of the pressure drop during density-wave oscillations in a single pressure drop oscillations cycle were considered. It has been shown that the proposed algorithm allows us to distinguish five types of non-stationary two-phase flow patterns, such as bubble flow, confined bubble flow, wavy annular flow, liquid flow, and slug flow. The flow pattern identification was confirmed by images obtained using a high-speed camera. Taking into consideration the oscillations between identified two-phase flow patterns, the four boiling regimes during a single cycle of the long-period pressure drop oscillations are classified. The obtained results show that the proposed combination of recurrence quantification analysis (RQA) and a self-organizing map (SOM) in the paper can be used to analyze changes in flow patterns in non-stationary boiling. It seems that the use of more complex algorithms of neural networks and their learning process can lead to the automation of the process of identifying boiling regimes in minichannel heat exchangers.
Highlights
The reduction in the size of components in cooling devices has led to a rapid increase in cooling heat flux
A self-organizing map combined with the recurrence quantification analysis was used to identify flow boiling patterns in a circular horizontal minichannel with a diameter of 1 mm
The obtained results show that the proposed method can be used to analyze changes in two-phase flow patterns in a non-stationary boiling
Summary
The reduction in the size of components in cooling devices has led to a rapid increase in cooling heat flux. The heat transfer mechanisms in mini- and microchannels are strongly related to the flow pattern dynamics This explains the recent increase in the number of studies addressing the identification of flow patterns based on image [15,16] or signal processing [17,18]. Used a combination of Lyapunov stability theory and numerical analysis to investigate dynamic features of excursive instability for forced two-phase boiling flow in a horizontal channel. In the previous paper [22], we used the combination of the windowed recurrence quantification analysis (RQA) and principal component analysis (PCA) to identify the occurrence of a dominant sequence of flow patterns. In the presented paper, a combination of a self-organizing map (SOM) with recurrence quantification analysis (RQA) was used to identify flow boiling patterns in a circular horizontal minichannel. To acquire images of different two-phase flow patterns in the flow boiling, a high-speed digital camera was used
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