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TECHNICAL PAPERS

Adaptive Selection of Aircraft Engine Technologies in the Presence of Risk

[+] Author and Article Information
B. A. Roth, M. D. Graham, D. N. Mavris

School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0150

N. I. Macsotai

GE Aircraft Engines, Cincinnati, OH 45215

J. Eng. Gas Turbines Power 126(1), 40-44 (Mar 02, 2004) (5 pages) doi:10.1115/1.1639006 History: Received December 01, 2001; Revised March 01, 2002; Online March 02, 2004
Copyright © 2004 by ASME
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References

Roth, B. A., German, B. J., and Mavris, D. N., 2001, “Adaptive Selection of Engine Technology Solution Sets From a Large Combinatorial Space,” 2001 AIAA/ASME/SAE Joint Propulsion Conference, Salt Lake City, UT, July 8–11, Paper No. AIAA2001-3208.
Roth, B., and Mavris, D. N., 2001, “Commercial Engine Architecture Selection in the Presence of Uncertainty and Evolving Requirements,” 15th International Society of Air Breathing Engines, Bangalore, India, Sept. 2–7, Paper No. ISABE2001-1169.
Kirby, M. R., and Mavris, D. N., 2000, “A Method for Technology Selection Based on Benefit, Available Schedule and Budget Resources,” 5th World Aviation Congress and Exposition, San Diego, Oct., Paper No. AIAA2000-01-5563.
Goldberg, D., 1989, Genetic Algorithms in Search, Optimization, & Machine Learning, Addison-Wesley, Reading, MA, p. 27.
Kirby, M. K., and Mavris, D. N., 1999, “Forecasting Technology Uncertainty in Preliminary Aircraft Design,” 4th World Aviation Congress and Exposition, San Francisco, CA, Oct. 19–21, Paper No. SAE1999-01-5631.

Figures

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K-σ model for technology readiness (from Kirby and Mavris, Ref. 5)
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Typical TIES representation of technology in terms of point estimates on K-factor deltas
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Calculation of technology benefit using the K-σ technology readiness model
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Converged technology solution set for shop cost+fuel burn objective function
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6000 nmi mission fuel burn convergence history for 50% shop cost+50% fuel burn objective weights
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Relative shop cost convergence history for 50% shop cost+50% fuel burn objective weights
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Converged technology solution set for 33% shop cost+33% fuel burn+33% TRL objective weights
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Converged technology solution set for shop cost+fuel burn objective function with K-σ risk model

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