Journal article
Selection and sequencing heuristics to reduce variance in gas turbine engine nozzle assemblies
European journal of operational research, Vol.132(3), pp.490-504
08/01/2001
DOI: 10.1016/S0377-2217(00)00139-9
Abstract
During the maintenance of gas turbine engines, the selection and placement of nozzle guide vanes about the circumference of a turbine nozzle greatly affects the efficiency and reliable operation of these engines. A number of research studies have addressed these selection and sequencing problems by essentially solving each problem independent of the other. The selection problem considers the maximization of the number of assembled nozzles that are feasible with respect to exit area requirements. Whereas, the sequencing problem considers the assignment of vanes, such that the variation in the throat area between adjacent vanes is minimized. However, the ability to obtain a sequence of vanes with a reasonably low variation in adjacent throat areas can, and often does, depend largely on the vanes that have been selected. Consequently, we propose and develop a selection methodology that not only accounts for feasibility with respect to exit area constraints, but also for the impact on the variation of the resulting sequence of vanes. The proposed methods are empirically compared to those of previous studies. These comparisons show that orders of magnitude reductions in expected engine operating costs are very likely.
Details
- Title: Subtitle
- Selection and sequencing heuristics to reduce variance in gas turbine engine nozzle assemblies
- Creators
- Patrick Johanns - Centre for Manufacturing Management, Melbourne Business School, 200 Leicester Street, Carlton, Vic. 3053, AustraliaTim Lowe - University of IowaRobert Plante - Purdue University West Lafayette
- Resource Type
- Journal article
- Publication Details
- European journal of operational research, Vol.132(3), pp.490-504
- DOI
- 10.1016/S0377-2217(00)00139-9
- ISSN
- 0377-2217
- eISSN
- 1872-6860
- Publisher
- Elsevier B.V
- Number of pages
- 15
- Language
- English
- Date published
- 08/01/2001
- Academic Unit
- Business Analytics
- Record Identifier
- 9984963109802771
Metrics
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