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Gas Turbine Mixer Modelling Strategies and Afterburner Liner Burn-Through Diagnostics
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0003-0739-8448
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-8466-356X
2019 (English)Conference paper, Published paper (Other academic)
Abstract [en]

A mixer may be damaged either by cracks or mechanical deformation causing a change in geometry. Only the latter case is, in some cases, possible to detect by shifts in physical measurements such as pressures and temperatures. In general, deformations of the geometry of a mixer due to damage is very hard to identify and quantify with the onboard measurements available, especially for turbofans with high bypass ratio (BPR) where a damaged mixer may cause a slight loss in thrust rather than shifts in measurable quantities.

A special case of mixer damage that may be detected is burn-through of the afterburner liner in low bypass afterburning turbofans. The liner is used to protect the outer casing of the gas turbine to the high temperatures during afterburner operation. For this, the liner need to be continuously cooled by bypass air to withstand the temperatures. A burn-through is generally caused by a local blockage of the cooling path, leading to temperatures the liner cannot withstand. In severe cases it may cause a burn-through of the gas turbine outer casing as well where it may cause a fire in the engine bay.

In this paper, two diagnostic routines are developed to identify a burn-through of an afterburner liner. The diagnostics is intended to be performed as a part of the startup check of the gas turbine to increase the confidence that no burn-through has occurred during the last operation. For these methods a mixer model of high enough fidelity is required, which is described in the paper. The main conclusion is that with enough data it is possible to detect a burn-through but the data collection time is so long that the methods need to be further enhanced to be of any practical use.

Place, publisher, year, edition, pages
2019.
Keywords [en]
Mixer, Modelling, Diagnostics, Afterburner, Burn-Through
National Category
Aerospace Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-45867OAI: oai:DiVA.org:mdh-45867DiVA, id: diva2:1366389
Conference
24:th ISABE Conference, Canberra, September 22-27, 2019
Projects
DIAGNOSIS
Funder
Knowledge Foundation, 20160133Available from: 2019-10-29 Created: 2019-10-29 Last updated: 2022-12-14Bibliographically approved
In thesis
1. On model based aero engine diagnostics
Open this publication in new window or tab >>On model based aero engine diagnostics
2023 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Maintenance and diagnostics play a vital role in the aviation sector. This is especially true for the engines, being one of the most vital components. Lack of maintenance, or poor knowledge of the current health status of the engines, may lead to unforeseen disruptions and possibly catastrophic effects. To keep track of the health status, and thereby supporting maintenance planning, model based diagnostics is a key factor. 

In the work going into this thesis, various aspects of model based gas turbine diagnostics, focused on aero engines, are covered. First, the importance of knowing what health parameters may be derived from a set of measurements is addressed. The selected combination is herein denoted as a matching scheme. A framework is proposed where the most suitable matching scheme is selected for a numerically robust diagnostic system. If a sensor malfunction is detected, the system automatically adapts.

The second subject is a system for detecting a burn-through of an afterburner inner liner. This kind of burn-through event has a very small impact on available on-board measurements, making it difficult to detect numerically. A method is proposed performing back-to-back testing after each engine start. The method has shown potential to detect major burn-through events under the preconditions, regarding data collection time and frequency. Increasing these will allow for more accurate estimations.

The third subject covers the importance of knowing the airplane installation effects. These are generally the intake pressure recovery, bleed and shaft power extraction. Just like inaccurate measurements affect diagnostic results, so does erroneous installation effects. A method for estimating said effects in the presence of gradual degradation has been proposed by using neural networks. By retraining the networks throughout the degradation process, the estimation errors is reduced, ensuring relevant estimations even at severe degradations.

Finally, an issue related to the general lack of on-board measurements for diagnostics is addressed. Due to lack of measurements, the diagnostic model tend to be underdetermined. A least square solver working without a priori information has been implemented and evaluated. Results from the solver is very much dependent on available instrumentation. In well instrumented components, such as the compressors, good diagnostic accuracy was achieved while the turbine health estimations suffer from smeared out results due to poor instrumentation.

Place, publisher, year, edition, pages
Västerås: Mälardalens universitet, 2023. p. 73
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 334
Keywords
Aero engines, model based diagnostics, gas path analysis
National Category
Aerospace Engineering
Research subject
Energy- and Environmental Engineering
Identifiers
urn:nbn:se:mdh:diva-61274 (URN)978-91-7485-578-4 (ISBN)
Presentation
2023-01-31, Gamma, Mälardalens universitet, Västerås, 09:00 (English)
Opponent
Supervisors
Funder
Knowledge Foundation
Available from: 2022-12-15 Created: 2022-12-14 Last updated: 2023-01-10Bibliographically approved

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Stenfelt, MikaelKyprianidis, Konstantinos

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