Efficient genetic algorithm based robust design method for compressor fan blades
Efficient genetic algorithm based robust design method for compressor fan blades
This paper presents an efficient genetic algorithm based methodology for robust design that produces compressor fan blades tolerant against erosion. A novel geometry modeling method is employed to create eroded compressor fan blade sections. A multigrid Reynolds-Averaged Navier Stokes (RANS) solver HYDRA with Spalart Allmaras turbulence model is used for CFD simulations to calculate the pressure losses. This is used in conjunction with Design of Experiment techniques to create Gaussian stochastic process surrogate models to predict the mean and variance of the performance. The Non-dominated Sorting Genetic Algorithm (NSGA-II) is employed for the multiobjective optimization to find the global Pareto-optimal front. This enables the designer to trade off between mean and variance of performance to propose robust designs.
1-9
Kumar, Apurva
9152d989-0e22-4bba-a1f2-93aa080b8766
Keane, A.J.
26d7fa33-5415-4910-89d8-fb3620413def
Nair, P.B.
d4d61705-bc97-478e-9e11-bcef6683afe7
Shahpar, S.
68625741-8304-4df1-96c6-08ee71dda686
2005
Kumar, Apurva
9152d989-0e22-4bba-a1f2-93aa080b8766
Keane, A.J.
26d7fa33-5415-4910-89d8-fb3620413def
Nair, P.B.
d4d61705-bc97-478e-9e11-bcef6683afe7
Shahpar, S.
68625741-8304-4df1-96c6-08ee71dda686
Kumar, Apurva, Keane, A.J., Nair, P.B. and Shahpar, S.
(2005)
Efficient genetic algorithm based robust design method for compressor fan blades.
ASME 2005 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, Long Beach, USA.
24 - 28 Sep 2005.
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
This paper presents an efficient genetic algorithm based methodology for robust design that produces compressor fan blades tolerant against erosion. A novel geometry modeling method is employed to create eroded compressor fan blade sections. A multigrid Reynolds-Averaged Navier Stokes (RANS) solver HYDRA with Spalart Allmaras turbulence model is used for CFD simulations to calculate the pressure losses. This is used in conjunction with Design of Experiment techniques to create Gaussian stochastic process surrogate models to predict the mean and variance of the performance. The Non-dominated Sorting Genetic Algorithm (NSGA-II) is employed for the multiobjective optimization to find the global Pareto-optimal front. This enables the designer to trade off between mean and variance of performance to propose robust designs.
Text
kuma_05.pdf
- Accepted Manuscript
More information
Published date: 2005
Additional Information:
DETC2005
Venue - Dates:
ASME 2005 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, Long Beach, USA, 2005-09-24 - 2005-09-28
Identifiers
Local EPrints ID: 23901
URI: http://eprints.soton.ac.uk/id/eprint/23901
PURE UUID: 00860703-52b6-4080-be78-52e84df192b9
Catalogue record
Date deposited: 30 Mar 2006
Last modified: 16 Mar 2024 02:53
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Contributors
Author:
Apurva Kumar
Author:
P.B. Nair
Author:
S. Shahpar
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