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Adaptive Selection of Aircraft Engine Technologies in the Presence of Risk

[+] Author Affiliations
Bryce Roth, Matthew Graham, Dimitri Mavris

Georgia Institute of Technology, Atlanta, GA

Noel Macsotai

GE Aircraft Engines, Cincinnati, OH

Paper No. GT2002-30623, pp. 147-152; 6 pages
doi:10.1115/GT2002-30623
From:
  • ASME Turbo Expo 2002: Power for Land, Sea, and Air
  • Volume 1: Turbo Expo 2002
  • Amsterdam, The Netherlands, June 3–6, 2002
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 0-7918-3606-1 | eISBN: 0-7918-3601-0
  • Copyright © 2002 by ASME

abstract

The objective of this paper is to describe a method for selecting optimal engine technology solution sets while simultaneously accounting for the presence of technology risk. This method uses a genetic algorithm in conjunction with Technology Identification, Evaluation, and Selection methods to find optimal combinations of technologies. The unique feature of this method is that the technology evaluation itself is probabilistic in nature. This allows the performance impact and associated risk of each technology to be quantified in terms of a distribution on key engine technology metrics. The resulting method can best be characterized as a concurrent genetic algorithm/Monte Carlo analysis that yields a performance- and risk-optimal technology solution set. This solution set is inherently a robust solution because the method will naturally strive to find those technologies representing the best compromise between performance improvement and technology risk. Finally, a practical demonstration of the method and accompanying results is given for a typical commercial aircraft engine technology selection problem.

Copyright © 2002 by ASME

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