A systematic approach for modelling modern turbofan engines

Master Thesis (2022)
Author(s)

S.S. Ramdin (TU Delft - Aerospace Engineering)

Contributor(s)

W.P.J. Visser – Mentor (TU Delft - Flight Performance and Propulsion)

J. Regueiro Cueva – Graduation committee member (KLM Engine Services)

Faculty
Aerospace Engineering
Copyright
© 2022 Shiv Ramdin
More Info
expand_more
Publication Year
2022
Language
English
Copyright
© 2022 Shiv Ramdin
Coordinates
52.311434, 4.797646
Graduation Date
13-10-2022
Awarding Institution
Delft University of Technology
Programme
['Aerospace Engineering | Flight Performance and Propulsion']
Sponsors
KLM Engine Services
Faculty
Aerospace Engineering
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Engine maintenance needs to be planned timely and strategically. This can only be done if the health of the engine can be predicted, which requires an accurate engine performance model. Developing such a model is becoming increasingly challenging, due to the reduced number of sensors in modern gas turbines. Besides this, a lot of data is proprietary and not available to the maintenance provider. This leads to the objective of the thesis: Improve Gas Path Analysis at KLM Engine Services, by developing a systematic approach for modelling modern turbofan engines using sensor measurements and general physical relations. For the on-design modelling general physical relations were used to bridge the gap caused by the reduced amount of data. The off-design modelling was done by scaling baseline maps from open literature using second order polynomials. The outcome was verified by developing two engine models in parallel and the validation was done using on-wing data.

Files

Thesis_ShivanRamdinV2.pdf
(pdf | 4.45 Mb)
- Embargo expired in 28-09-2024
License info not available