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RESEARCH PAPERS

Robust Design of Compressor Fan Blades Against Erosion

[+] Author and Article Information
Apurva Kumar, Andy J. Keane

Computational Engineering and Design Group, School of Engineering Sciences, University of Southampton, Highfield, Southampton SO17 1BJ, UK

Prasanth B. Nair1

Computational Engineering and Design Group, School of Engineering Sciences, University of Southampton, Highfield, Southampton SO17 1BJ, UKp.b.nair@soton.ac.uk

Shahrokh Shahpar

Aerothermal Methods, Rolls-Royce Plc. Derby, DE24 8BJ, UK

1

Corresponding author.

J. Mech. Des 128(4), 864-873 (Jan 18, 2006) (10 pages) doi:10.1115/1.2202886 History: Received September 16, 2005; Revised January 18, 2006

This paper is concerned with robust aerodynamic design of compressor blades against erosion. The proposed approach combines a multiobjective genetic algorithm with geometry modeling methods, high-fidelity computational fluid dynamics, and surrogate models to arrive at robust designs on a limited computational budget. The multiobjective formulation used here allows explicit trade-off between the mean and variance of the performance to be carried out. Detailed numerical studies are presented for robust geometric design of a typical compressor fan blade section to illustrate the proposed methodology. The performance of a selected robust optimal solution on the Pareto front is compared to a deterministic optimal solution to demonstrate that significant improvements in the mean shift and variance can be achieved.

Copyright © 2006 by American Society of Mechanical Engineers
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Figures

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Figure 1

Blades with variations in noise factors

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Figure 2

Blades with variations in control factors

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Figure 3

A typical C-O-H mesh used for CFD analysis

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Figure 4

CFD static pressure plot

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Figure 5

The scatter plot of pressure loss using the training data set

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Figure 6

Predicted posterior mean versus observed values (R2=0.954)

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Figure 7

SCVRi values using leave-one-out validation

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Figure 8

Probability distribution of the pressure loss using MCS

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Figure 9

Main effect plot for location

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Figure 10

Main effect plot for width

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Figure 11

Main effect plot for height

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Figure 12

Flowchart for robust design methodology

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Figure 13

Flowchart for deterministic surrogate-assisted design optimization

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Figure 14

Baseline and optimal blade shapes

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Figure 15

Histogram of pressure loss in presence of erosion

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Figure 16

Plot of the initial data set with the initial Pareto front and all the search points. The plot also shows the last three Pareto fronts after which the search was terminated. Note that the 11th, 12th, and 13th Pareto fronts are the same and overlap, hence they are not distinguishable in the plot.

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Figure 17

Shape of robust and baseline geometry

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Figure 18

Histogram of pressure loss of the robust geometry

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Figure 19

Histograms of robust and deterministic optimal geometries

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