Optimisation of aero gas turbine engines

Authors
Citation
A. Guha, Optimisation of aero gas turbine engines, AERONAUT J, 105(1049), 2001, pp. 345-358
Citations number
21
Categorie Soggetti
Aereospace Engineering
Journal title
AERONAUTICAL JOURNAL
ISSN journal
00019240 → ACNP
Volume
105
Issue
1049
Year of publication
2001
Pages
345 - 358
Database
ISI
SICI code
0001-9240(200107)105:1049<345:OOAGTE>2.0.ZU;2-2
Abstract
A systematic methodology for the thermodynamic optimisation of civil bypass engines (turbofan or advanced propulsors) is presented, which would be use ful for designing air-breathing engines based on "clean-sheet analysis". Th e process starts with establishing an optimum specific thrust for the engin e based on an economic analysis (installation constraints, noise regulation s etc. also need to be considered). The task of the optimisation process is then to find the combination of optimum values of fan pressure ratio, over all pressure ratio, bypass ratio and turbine entry temperature concurrently that maximises overall efficiency at the fixed specific thrust. This proce dure is quite different from the usual single-variable parametric performan ce studies which do not give proper optimum values and may involve large ex cursion in the value of the specific thrust unacceptable for a particular m ission. Additionally, several, simple and explicit, analytical relations ar e derived here from fundamental principles, which perform well against nume rical optimisation performed by a specialist computer program employing ite rative and advanced search techniques. The analytical relations accelerate the optimisation process and offer physical insight. Present numerical comp utations with real gas properties have established new concepts in turbofan optimisation (for example, the existence of an optimum bypass ratio and op timum turbine entry temperature). The question of optimum jet velocity has been addressed. An analytical expression for the optimum jet velocity at a given bypass ratio has been derived which performs well against numerical o ptimisation results.