# Boiling Flow Pattern Identification Using a Self-Organizing Map
## 1 Introduction  
The reduction in the size of components in cooling devices has led to a rapid increase in cooling heat flux. The miniaturization of devices requires the application of a cooling channel with a very small diameter. Using microchannels in small cooling systems can help decrease the amount of refrigerant and increase heat dissipation rates [1; 2]. A flow boiling can dissipate high heat fluxes, but boiling in small channels causes problems with the control of the process. In [3; 4], the occurrence of different types of the instability of two-phase flow in mini- and microchannels were noticed. The instabilities cause fluctuations in pressure drop and channel wall temperature (periodic or non-periodic). Many researchers numerically investigated the mass and heat transfer during flow boiling in various cases. [PERSON] et al. numerically analyzed the influence of channel inclination on the critical heat flux [5]. Moreover, the phase change phenomena of boiling flow inside the tube with porous medium was investigated using the Eulerian-Eulerian multi-phase Rensselaer Polytechnic Institute (RPI) [6]. [PERSON] et al., using a molecular dynamic simulation, defined the effect of silver nanoparticles' number on the boiling of Argon in the microchannel [7]. During boiling instabilities, the various two-phase flow patterns were observed in variously enhanced microchannels, e.g., in channels with porous walls [8], in channels with triangular corrugations [9]. Many studies report that different types of instabilities are superimposed on each other [10; 11; 12]. There are articles concerning flow pattern transition models [13]and flow regime mapping [14]. However, further analysis of flow patterns is still needed, especially for unstable processes [14]. 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]. To identify the flow patterns in air-water two-phase flow, the Kohonen self-organizing map was applied in paper [19]. However, in this paper, eight linear stochastic features were used to identify flow patterns. Therefore, the usage of linear time series analysis to study such complex signals in many cases could be insufficient, and non-linear time series analysis techniques are increasingly used for such data. In the paper [20], a multi-scale entropy was applied to identify flow regimes in pressure-difference signals. Moreover, the gas-liquid transition boundary for slug-wave and boiling wave flow was defined. [PERSON] et al. [21] 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. On the basis, conducted analysis to map of the dynamical properties of two-phase flow patterns was constructed. In general _RQA_ (using the Matlab Toolbox) returns 11 coefficients. Each of them characterizes a different aspect of the considered system dynamics. A universal method of _RQA_ coefficient selection for further analysis has not been developed. The process of two-phase flow pattern identification requires taking into consideration the combination of several coefficients at once. The _PCA_ transfers an input set of data (_RQA_ coefficients) into a new set of data. The coordinates of this new set of data are called the principal components. Usually, the first few components explain most of the input data variation. The principal component analysis is only a simple data transformation method. This is the reason that, instead of the _PCA_ method, a new method of analysis of _RQA_ results is necessary.