MATEC Web Conf.
Volume 220, 20182018 The 2nd International Conference on Mechanical, System and Control Engineering (ICMSC 2018)
|Number of page(s)||7|
|Section||Power Machinery Engineering|
|Published online||29 October 2018|
Experimental Compressor Multidisciplinary Optimization Using Different Parameterization Schemes
1 Deputy General Designer, Lyulka Design Bureau, Moscow, Russia
2 Department of Technologies of Aircraft GTE Modeling, Central Institute of Aviation Motors Named after P.I. Baranov, Moscow, Russia
3 Department of Aircraft Engines Theory, Samara University, Samara, Russia
The present-day compressors development is a labor-intensive problem, because compressor structure should meet different requirements to the design characteristics. It’s reasonable to find optimal combination of compressor design parameters using the mathematical optimization resources. In this paper the multi-criteria optimization of the rotor and stator blades of the experimental compressor stage NASA Rotor 37 is carried out. The goal of this work is the analysis of different blade parameterization schemes and determination of optimum number of variable parameters for compressor stage aerodynamic characteristics improvement. As an optimization criterions efficiency of compressor stage was used. Flow rate and pressure ratio values should not exceed base values more than ±0.5%. In order to research an effect of the number of variables to the optimization results, the four parameterized models were created. The optimization of the NASA Rotor 37 was carried out using all created parametric models. The models are characterized by number of variables, which describe the blade pressure and suction sides. As a result of optimization the NASA Rotor 37 version was found, which provide the efficiency increasing by approximately 2% while all aerodynamic and requirements are satisfied. It was also found, that increasing of the blade profile number of variables more than 14 is not rational.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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