Exploring the Fitness Landscape of a Realistic Turbofan Rotor Blade Optimization
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F19%3A73589830" target="_blank" >RIV/61989592:15310/19:73589830 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-97773-7_46" target="_blank" >http://dx.doi.org/10.1007/978-3-319-97773-7_46</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-97773-7_46" target="_blank" >10.1007/978-3-319-97773-7_46</a>
Alternative languages
Result language
angličtina
Original language name
Exploring the Fitness Landscape of a Realistic Turbofan Rotor Blade Optimization
Original language description
Aerodynamic shape optimization has established itself as a valuable tool in the engineering design process to achieve highly efficient results. A central aspect for such approaches is the mapping from the design parameters which encode the geometry of the shape to be improved to the quality criteria which describe its performance. The choices to be made in the setup of the optimization process strongly influence this mapping and thus are expected to have a profound influence on the achievable result. In this work we explore the influence of such choices on the effects on the shape optimization of a turbofan rotor blade as it can be realized within an aircraft engine design process. The blade quality is assessed by realistic three dimensional computational fluid dynamics (CFD) simulations. We investigate the outcomes of several optimization runs which differ in various configuration options. We compare the results from the covariance matrix adaptation evolutionary strategy (CMA-ES) with the outcome of a particle swarm optimization (PSO). We also investigate the changes induced by a different initialization of the CMA-ES and by a variation of its population size. A particular focus is put on the variation of the results if we use different number of degrees of freedom for parametrization of the rotor blade geometry. For all such variations, we generally find that the achievable improvement of the blade quality is comparable for most settings and thus rather insensitive to the details of the setup. On the other hand, even supposedly minor changes in the settings, such as using a different random seed for the initialization of the optimizer algorithm, lead to very different shapes. Optimized shapes which show comparable performance usually differ quite strongly in their geometries over the complete blade. Our analyses indicate that the fitness landscape for such a realistic turbofan rotor blade optimization is highly multi-modal with many local optima, where very different shapes show similar performance.
Czech name
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Czech description
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Classification
Type
C - Chapter in a specialist book
CEP classification
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OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
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Continuities
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Book/collection name
EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization
ISBN
978-3-319-97773-7
Number of pages of the result
13
Pages from-to
510-522
Number of pages of the book
1475
Publisher name
Springer International Publishing
Place of publication
Cham
UT code for WoS chapter
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