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Axial compressor rotor optimization using a novel ensemble of surrogates-based infill criterion

Axial compressor rotor optimization using a novel ensemble of surrogates-based infill criterion
Axial compressor rotor optimization using a novel ensemble of surrogates-based infill criterion
A new infill criterion for so-called ensemble of surrogates based optimization is proposed and put to the test in practice to aerodynamically optimize a compressor rotor. The optimization method takes advantage of five radial basis functions using a weighted linear combination. This set of radial basis functions
making up the ensemble across the design space is dynamically changed using the maximization of a custom metric based on the local surrogate’s agreement and the global accuracy of each ensemble combination. The selected ensemble is then searched using a hybrid optimizer, viz., a global genetic algorithm and local SQP searches, and finally the optimal points are evaluated using the rotor’s black box function. The results are compared with established optimization approaches. The best design is analysed further in terms of the flow physics. Similar to a realistic industrial setting, the constrained, single-objective shape optimization of NASA Rotor 37 involves 25 design variables with a limited computational budget.
Kamenik, Jan
6a80b527-28d9-492c-9e50-91b4000c881b
Stramacchia, Michele
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Toal, David J.J.
dc67543d-69d2-4f27-a469-42195fa31a68
Keane, Andy J.
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Bates, Ron
f3439cad-2150-43de-8513-d5fc90317be7
Kamenik, Jan
6a80b527-28d9-492c-9e50-91b4000c881b
Stramacchia, Michele
a82506fd-6885-4567-a510-17e3fbb46ef2
Toal, David J.J.
dc67543d-69d2-4f27-a469-42195fa31a68
Keane, Andy J.
26d7fa33-5415-4910-89d8-fb3620413def
Bates, Ron
f3439cad-2150-43de-8513-d5fc90317be7

Kamenik, Jan, Stramacchia, Michele, Toal, David J.J., Keane, Andy J. and Bates, Ron (2017) Axial compressor rotor optimization using a novel ensemble of surrogates-based infill criterion. 2017 Gas Turbine India Conference, , Bangalore, India. 07 - 08 Dec 2017. 12 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

A new infill criterion for so-called ensemble of surrogates based optimization is proposed and put to the test in practice to aerodynamically optimize a compressor rotor. The optimization method takes advantage of five radial basis functions using a weighted linear combination. This set of radial basis functions
making up the ensemble across the design space is dynamically changed using the maximization of a custom metric based on the local surrogate’s agreement and the global accuracy of each ensemble combination. The selected ensemble is then searched using a hybrid optimizer, viz., a global genetic algorithm and local SQP searches, and finally the optimal points are evaluated using the rotor’s black box function. The results are compared with established optimization approaches. The best design is analysed further in terms of the flow physics. Similar to a realistic industrial setting, the constrained, single-objective shape optimization of NASA Rotor 37 involves 25 design variables with a limited computational budget.

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Accepted/In Press date: 18 August 2017
Published date: 7 December 2017
Venue - Dates: 2017 Gas Turbine India Conference, , Bangalore, India, 2017-12-07 - 2017-12-08

Identifiers

Local EPrints ID: 413782
URI: http://eprints.soton.ac.uk/id/eprint/413782
PURE UUID: b20c004f-b27b-4e80-ae8a-ae37a9c24d16
ORCID for David J.J. Toal: ORCID iD orcid.org/0000-0002-2203-0302
ORCID for Andy J. Keane: ORCID iD orcid.org/0000-0001-7993-1569

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Date deposited: 06 Sep 2017 16:31
Last modified: 16 Mar 2024 03:55

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Contributors

Author: Jan Kamenik
Author: Michele Stramacchia
Author: David J.J. Toal ORCID iD
Author: Andy J. Keane ORCID iD
Author: Ron Bates

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