Method for identifying flow type of soft grain two-phase turbulence based on artificial intelligence
A flow pattern recognition and artificial intelligence technology, applied in neural learning methods, flow characteristics, biological neural network models, etc., can solve the problems of poor applicability, low reliability, low accuracy, etc., to improve efficiency and accuracy, The effect of reducing costs and reducing subjectivity factors
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 In conjunction with the accompanying drawings, the present invention will be described in detail below.
 refer to Figure 1~Figure 6 , an artificial intelligence-based method for identifying two-phase turbulent flow patterns of soft abrasive particles. By using the simulation technology that combines the Euler model and the renormalization group (RNG) two-equation model, it can obtain the two-phase turbulent flow of soft abrasive particles. The objective mathematical description of various flow pattern characteristics and the change law of characteristic parameters in the process of flow pattern transformation, according to the quantitative analysis of wavelet packets, the eigenvectors formed by the obtained parameters are used to input probabilistic neural network (PNN) for training and identification, and realize turbulent flow. Type objective identification and classification. It generally includes the acquisition of soft abrasive two-phase turbulent pressur...
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