This study presents the mechanical efficiency optimization of a sliding vane rotary compressor by using genetic algorithms. Relevant air properties, volume segments, vane loadings and stresses, friction forces, compression power, and power loss are calculated to determine the mechanical efficiency of a compressor. Design variables include the major axis length and minor axis length of the elliptical stator inner contour, thickness, depth and width of vanes, mechanical efficiency, rotor rotational speed, polytropic exponent, and angular locations of the inlet and outlet ports. The effects of the mutation rate, crossover rate, and population size of the genetic algorithms on these design variables are studied. The vane is thin and the variation effects of vane dimensions on the mechanical efficiency of the compressor are less significant than other design variables. Therefore, the dimensions of vanes can be eliminated as design variables. The mechanical efficiency of the compressor is 0.55. The optimum values of these design variables are recommended for further development of the compressor.
Issue Section:
Operations, Applications & Components
Keywords:
compressor,
optimization,
rotary vane,
genetic algorithms,
blades,
compressors,
genetic algorithms
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.Copyright © 2009
by American Society of Mechanical Engineers
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