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High-Accuracy Matching of Engine Performance Models to Test Data

[+] Author Affiliations
Bryce Roth, Dimitri Mavris

Georgia Institute of Technology, Atlanta, GA

David L. Doel, Don Beeson

GE Aircraft Engines

Paper No. GT2003-38784, pp. 129-137; 9 pages
doi:10.1115/GT2003-38784
From:
  • ASME Turbo Expo 2003, collocated with the 2003 International Joint Power Generation Conference
  • Volume 1: Turbo Expo 2003
  • Atlanta, Georgia, USA, June 16–19, 2003
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 0-7918-3684-3 | eISBN: 0-7918-3671-1
  • Copyright © 2003 by ASME

abstract

Matching of cycle models to test results for gas turbine engines is fundamentally an exercise in optimal robust parameter estimation. The problem is inherently nondeterministic in nature, so it stands to reason that probabilistic information can be used to secure improved match accuracy if properly employed. This paper proposes an approach to status matching that eliminates the need for parameter weightings, gives an intuitive feel for the results in terms of probabilistic parameters, utilizes all available information (probabilistic and deterministic), and yields high-accuracy matches between model prediction and experiment. The method development begins with a typical sum-squared errors approach and subsequently builds on this. A deviation penalty function formulation is introduced to improve solution conditioning and a multi-objective measure of fit based on the Z-score is introduced. Several measures of model fit are compared including summed-squared errors, minimax, and sum absolute error formulations. This approach is first demonstrated for a simple cantilever beam parameter-matching problem, and is later discussed in the context of turbofan engine matching.

Copyright © 2003 by ASME
Topics: Engines

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