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An Overview of Prognosis Health Management Research at GRC for Gas Turbine Engine Structures With Special Emphasis on Deformation and Damage ModelingHerein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include 1) diagnostic/detection methodology, 2) prognosis/lifing methodology, 3) diagnostic/prognosis linkage, 4) experimental validation and 5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multi-mechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.
Document ID
Document Type
Arnold, Steven M. (NASA Glenn Research Center Cleveland, OH, United States)
Goldberg, Robert K. (NASA Glenn Research Center Cleveland, OH, United States)
Lerch, Bradley A. (NASA Glenn Research Center Cleveland, OH, United States)
Saleeb, Atef F. (Akron Univ. Akron, OH, United States)
Date Acquired
September 8, 2013
Publication Date
January 1, 2009
Subject Category
Aircraft Propulsion and Power
Report/Patent Number
Meeting Information
Annual Conference of the Prognostices and Health Management Society 2009(San Diego, CA)
Funding Number(s)
WBS: WBS 645846.
Distribution Limits
Public Use Permitted.

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