Abstract
The article discusses the issue of using neural networks to analyze the nature of the movement of droplets in the interblade channels of turbomachines. An experimentally verified computational model was used to analyze the parameters affecting the process under study. A set of 23 independent parameters was identified. They included both regime parameters and geometric ones. The presented set of parameters uniquely determines the behavior of a liquid particle moving through the channels of turbomachine cascades. The applicability of neural networks to analyze the behavior of droplets in the interblade channels of turbomachines is considered. For this purpose, a neural network was created that predicts the proportion of secondary droplets formed during the interaction of primary moisture with the surface of a turbine blade.
Published Version
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