Incorporation of a Probabilistic Monotonic Strain Energy Analysis to a Lifting Method
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TECHNICAL ARTICLE—PEER-REVIEWED
Incorporation of a Probabilistic Monotonic Strain Energy Analysis to a Lifing Method Onome Scott-Emuakpor • Tommy George • Todd Letcher • M.-H. Herman Shen • Charles Cross
Submitted: 14 December 2011 / Published online: 30 December 2011 Ó ASM International 2011
Abstract The proposed work analyzes the possibility of improving the capabilities of an energy-based fatigue life prediction method. The improvement being addressed is regarding the variation of empirical monotonic strain energy density calculations and the effects on the energybased fatigue life prediction capability. Since the prediction method was developed from the concept that the strain energy accumulated during both monotonic failure and an entire fatigue process are equal, meaning the strain energy accumulated during monotonic failure is a physical damage quantity, it was important to understand the variation of monotonic strain energy density. The process for incorporating this variation into the prediction method explores a probabilistic, Three-Sigma analysis that is applicable for all deterministic methods of measuring experimental monotonic strain energy density. The accuracy of the probabilistic energy-based lifing method was admirably assessed by comparison with experimental fatigue life results, between 103 and 105 cycles, conducted on Titanium 6Al–4V specimens at room temperature. Keywords
Fatigue Lifing Strain-energy Three-Sigma
Reprinted with permission from Enabling Sustainable Systems, Proceedings for the MFPT: The Applied Systems Health Management Conference 2011, Society for Machinery Failure Prevention Technology, 2011, pp. 525–536. O. Scott-Emuakpor (&) T. George C. Cross AFRL/RZTS, WPAFB, Dayton, OH 45433, USA e-mail: [email protected] T. Letcher M.-H.H. Shen Department of Mechanical and Aerospace Engineering, The Ohio State University, Columbus, OH 43210, USA
Introduction Design procedures of gas turbine engine components place a strong emphasis on the modeling of material behavior. A key material behavior in this procedure is the characteristic of fatigue life. The widely used design tools for characterizing fatigue life are the modified Goodman diagram and a stress vs. fatigue life (S–N) curve [1, 2]. For an accurate characterization of fatigue life, tens to hundreds of experimental results are required to construct Goodman diagrams and S–N curves. Depending on the desired lifing limit, significantly long time periods could be necessary to gather these experimental results. Therefore, a fatigue life prediction method that would require considerably less data and time than conventional empirical fatigue data would be an improvement to the aforementioned design tools. In order to reduce the amount of empirical data necessary to construct a fatigue life design tool, the discovery of a physical fatigue damage quantity was required. The simplest way to attain a damage quantity that is cumulative with fatigue cycles is by exploring the correlation between fatigue life and e
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