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TECHNICAL BRIEF

Applying Multiobjective Cost and Weight Optimization to the Initial Design of Turbine Disks

[+] Author and Article Information
A. R. Rao, J. P. Scanlan, A. J. Keane

Rolls-Royce University Technology Partnership for Design, CEDG, School of Engineering Sciences, University of Southampton, Hants SO17 1BJ, UK

http://www.soton.ac.uk/∼ajk/options/welcome.html

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http://www.ugs.com/products/nx/

Loads and speeds are representative of the values used in the design of the disk for modern turbofan engines.

J. Mech. Des 129(12), 1303-1310 (Feb 13, 2007) (8 pages) doi:10.1115/1.2779899 History: Received May 24, 2006; Revised February 13, 2007

Aerospace design optimization typically explores the effects of structural performance and aerodynamics on the geometry of a component. This paper presents a methodology to incorporate manufacturing cost and fatigue life models within an integrated system to simultaneously trade off the conflicting objectives of minimum weight and manufacturing cost while satisfying constraints placed by structural performance and fatigue. A case study involving the design of a high pressure turbine disk from an aircraft engine is presented. Manufacturing cost and fatigue life models are developed in DECISIONPRO ™, a generic modeling tool, whereas finite element analysis is carried out in the Rolls-Royce PLC proprietary solver SC03. A multiobjective optimization approach based on the nondominated sorting genetic algorithm (NSGA ) is used to evaluate the Pareto front for minimum cost and volume designs. A sequential workflow of the different models embedded within a scripting environment developed in MATLAB ™ is used for automating the entire process.

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Copyright © 2007 by American Society of Mechanical Engineers
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References

Figures

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Figure 9

The Pareto front

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Figure 10

Designs 1, 2, and 3

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Figure 6

Hoop stress contours for the initial design in SC03

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Figure 7

Radial stress contours for the initial design in SC03

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Figure 8

The design process sequence

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Figure 1

An axisymmetric section of the HPT disk

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Figure 2

HPT disk cost model in DECISIONPRO

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Figure 3

2D axisymmetric section of the disk showing design variables used in optimization

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Figure 4

Examples of parametrically modified geometries

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Figure 5

Typical FE mesh in SC03, showing adaptive refinement

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