An Overview of Prognosis Health Management Research at GRC for Gas Turbine Engine Structures with Special Emphasis on Deformation and Damage Modeling



Published Mar 26, 2021
Drs. Steven M. Arnold Robert K. Goldberg Bradley A. Lerch Atef F. Saleeb


Herein 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.*

How to Cite

M. Arnold, D. S., K. Goldberg, R., A. Lerch, B., & F. Saleeb, A. (2021). An Overview of Prognosis Health Management Research at GRC for Gas Turbine Engine Structures with Special Emphasis on Deformation and Damage Modeling. Annual Conference of the PHM Society, 1(1). Retrieved from
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model based diagnostics, model based prognostics, structural health monitoring

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