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Multi-objective optimum design of an aero engine rotor system using hybrid genetic algorithm
Published in Institute of Physics Publishing
2019
Volume: 624
   
Issue: 1
Abstract
A working aero engine rotor system is subjected to multi-objective optimisation using Genetic Algorithm based optimisation. A Hybrid Genetic Algorithm (HGA) is introduced to reduce the weight and unbalance response of the rotor system with constrain on critical speed. The existing aero engine gear box casing vibration is found to be within the critical speed constraint and additional constraints are imposed to move the critical away from this zone. Bearing-pedestal model and Rayleigh damping model are used for accurate results. The optimisation resulted in Pareto optimal solutions and best solution selected using utopia point concept. The outcome of the paper is a comparative study which highlights the advantages of HGA over Controlled Elitist Genetic Algorithm (CEGA) and Goal Programming (GP). © 2019 IOP Publishing Ltd. All rights reserved.
About the journal
JournalIOP Conference Series: Materials Science and Engineering
PublisherInstitute of Physics Publishing
ISSN17578981
Open AccessYes
Concepts (16)
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    Aircraft engines
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    Engines
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    Genetic algorithms
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    Linear programming
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    Pareto principle
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    Power transmission
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    Vibrations (mechanical)
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    Comparative studies
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    CRITICAL SPEED
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    Goal programming
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    HYBRID GENETIC ALGORITHMS
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    MULTI-OBJECTIVE OPTIMUM DESIGNS
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    Pareto optimal solutions
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    RAYLEIGH DAMPING MODEL
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    UNBALANCE RESPONSE
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    Multiobjective optimization