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| Content Provider | The American Society of Mechanical Engineers (ASME) Digital Collection |
|---|---|
| Author | Ma, Sang-Bum Kim, Kwang-Yong |
| Copyright Year | 2018 |
| Abstract | In order to extend the operating range of a centrifugal compressor, inclined discrete cavities located upstream of the impeller leading edge were optimized in this work. Aerodynamic performance analysis was performed using three-dimensional Reynolds-averaged Navier-Stokes equations with the shear stress transport turbulence model. A parametric study on aerodynamic performances of the centrifugal compressor with the inclined discrete cavities was conducted with six geometrical parameters. Through the parametric study, three geometric parameters were selected as design variables for optimization. Peak adiabatic efficiency and stall margin were selected as objective functions. The Latin hypercube sampling method was used to select the design points, and the radial basis neural network was used to construct surrogate models of the objective functions. A hybrid method combining the particle swarm optimization showed better overall performance in finding global optimum than the genetic algorithm. Pareto-optimal solutions provided the designs which enhance considerably both the performance parameters compared to the reference design. |
| Sponsorship | International Gas Turbine Institute |
| File Format | |
| ISBN | 9780791851029 |
| DOI | 10.1115/GT2018-76076 |
| Volume Number | Volume 2D: Turbomachinery |
| Conference Proceedings | ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition |
| Language | English |
| Publisher Date | 2018-06-11 |
| Publisher Place | Oslo, Norway |
| Access Restriction | Subscribed |
| Subject Keyword | Turbulence Navier-stokes equations Artificial neural networks Pareto optimization Compressors Particle swarm optimization Optimization Genetic algorithms Design Cavities Impellers Shear stress Sampling methods |
| Content Type | Text |
| Resource Type | Article |
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