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.
Adaptive Selection of Aircraft Engine Technologies in the Presence of Risk
Contributed by the International Gas Turbine Institute (IGTI) of THE AMERICAN SOCIETY OF MECHANICAL ENGINEERS for publication in the ASME JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Paper presented at the International Gas Turbine and Aeroengine Congress and Exhibition, Amsterdam, The Netherlands, June 3–6, 2002; Paper No. 2002-GT-30623. Manuscript received by IGTI, Dec. 2001, final revision, Mar. 2002. Associate Editor: E. Benvenuti.
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Roth , B. A., Graham , M. D., Mavris, D. N., and Macsotai, N. I. (March 2, 2004). "Adaptive Selection of Aircraft Engine Technologies in the Presence of Risk ." ASME. J. Eng. Gas Turbines Power. January 2004; 126(1): 40–44. https://doi.org/10.1115/1.1639006
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