Vaneless diffusers characteristics simulating by means of neural networks

International Conference on Compressors and their Systems 2019

Nikiforov, A.^1 ; Avramenko, D.^1 ; Kuchumov, A.^1 ; Terentev, S.^1 ; Galerkin, Yu^2 ; Solovyeva, O.^2

Department of Mechanization, Smolensk State Agricultural Academy, Bolshaja Sovetskaja, 10/2, Smolensk

214000, Russia^1

RandD Laboratory gas Dynamics of Turbo Machines Peter, Great St. Petersburg Polytechnic University, Polytechnicheskaya 29, St. Petersburg, Russia^2

关键词: CFD (computational fluid dynamics);    Conversion process;    Data normalization;    Gas dynamic parameters;    Neural networks trainings;    Preparation and processing;    Similarity criteria;    Velocity coefficients;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/604/1/012046/pdf
DOI  :  10.1088/1757-899X/604/1/012046

来源: IOP

【 摘 要 】

The paper presents the results of simulation of loss coefficient and the angle of flow at the outlet of diffuser in centrifugal compressor vaneless diffusers. The calculation was performed in a wide range of design and gas-dynamic parameters by means of neural networks. Also, an analysis performed by CFD (Computational Fluid Dynamics) methods is presented. In order to obtain mathematical models, a data sampling was used for vaneless diffusers with the following characteristics: relative width is b2/ D2= 0.014 - 0.1, outlet relative diameter is D4/ D2= 1.4 - 2.0, inlet flow angle is 2 α2= 10 - 90 , velocity coefficient is λc2 = 0.39 - 0.82, Reynolds numbers corresponding to them are Re b2 = 87 500 - 1 030 000. In order to improve the accuracy of simulating using neural networks, various recommendations on the preparation and processing of initial data were collected and tested: identification of conflict samples and outliers, data normalization, improving the quality of the neural networks training under the insufficient amount of sampling, etc. Application of the listed recommendations and an essential expansion of mathematical models definition significantly improved the accuracy of simulating. A simulation experiment based on neural models for studying the influence of dimensions, diffuser shape, and similarity criteria made it possible to check the physical adequacy of mathematical models, to obtain new data on energy conversion processes and to establish a number of recommendations on the optimal design of vaneless diffusers.