Title:
Estimation of Turbofan Engine Performance Model Accuracy and Confidence Bounds

dc.contributor.author Roth, Bryce Alexander en_US
dc.contributor.author Mavris, Dimitri N. en_US
dc.contributor.author Doel, David L. en_US
dc.contributor.corporatename International Society for Air Breathing Engines
dc.date.accessioned 2005-05-26T14:01:47Z
dc.date.available 2005-05-26T14:01:47Z
dc.date.issued 2003-09 en_US
dc.description Presented at the 2003 ISABE Conference, Sept. 1-4, Cleveland, OH. en_US
dc.description.abstract This paper explores the application of Inference and Bayesian Updating principles as a means to efficiently incorporate probabilistic data into the turbine engine status model matching process. This approach allows efficient estimation of nominal model match parameters from test data and also enables quantification of model accuracy and confidence bounds. The basic concepts are developed in detail and formulated into a status matching approach. This method is then applied to a simple surrogate matching problem using a cantilever beam matching exercise to illustrate the methods in a clear and easy-to-understand way. Typical results are presented and are directly analogous to status matching of a gas turbine engine cycle model. en_US
dc.format.extent 368046 bytes
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/6321
dc.language.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.publisher Georgia Institute of Technology
dc.publisher.original International Society for Air Breathing Engines (ISABE)
dc.relation.ispartofseries ASDL; ISABE-2003-1208 en_US
dc.relation.ispartofseries ASDL; ISABE-2003-1208
dc.subject Turbofan engines en_US
dc.subject Engine design en_US
dc.subject Performance prediction en_US
dc.subject Probabilistic analysis en_US
dc.title Estimation of Turbofan Engine Performance Model Accuracy and Confidence Bounds en_US
dc.type Text
dc.type.genre Paper
dspace.entity.type Publication
local.contributor.author Mavris, Dimitri N.
local.contributor.corporatename Daniel Guggenheim School of Aerospace Engineering
local.contributor.corporatename Aerospace Systems Design Laboratory (ASDL)
local.contributor.corporatename College of Engineering
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relation.isOrgUnitOfPublication a348b767-ea7e-4789-af1f-1f1d5925fb65
relation.isOrgUnitOfPublication a8736075-ffb0-4c28-aa40-2160181ead8c
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