4.7 Article

An energy-based microstructure model to account for fatigue scatter in polycrystals

Journal

JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS
Volume 59, Issue 3, Pages 595-609

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jmps.2010.12.014

Keywords

Fatigue crack initiation-life prediction; Grain boundaries; Microstructures; Polycrystalline material; Energy methods; Scatter

Funding

  1. Rolls-Royce Corporation
  2. National Science Foundation [DMR 08-03270]
  3. Division Of Materials Research
  4. Direct For Mathematical & Physical Scien [0803270] Funding Source: National Science Foundation

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Scatter observed in the fatigue response of a nickel-based superalloy, U720, is linked to the variability in the microstructure. Our approach is to model the energy of a persistent slip band (PSB) structure and use its stability with respect to dislocation motion as our failure criterion for fatigue crack initiation. The components that contribute to the energy of the PSB are identified, namely, the stress field resulting from the applied external forces, dislocation pile-ups, and work-hardening of the material is calculated at the continuum scale. Further, energies for dislocations creating slip in the matrix/precipitates, interacting with the GBs, and nucleating/agglomerating within the PSB are computed via molecular dynamics simulations. Through this methodology, fatigue life is predicted based on the energy of the PSB, which inherently accounts for the microstructure of the material. The present approach circumvents the introduction of uncertainty principles in material properties. It builds a framework based on mechanics of microstructure, and from this framework, we construct simulated microstructures based on the measured distributions of grain size, orientation, neighbor information, and grain boundary character, which allows us to calculate fatigue scatter using a deterministic approach. The uniqueness of the approach is that it avoids the large number of parameters prevalent in previous fatigue models. The predicted lives are in excellent agreement with the experimental data validating the model capabilities. (C) 2010 Elsevier Ltd. All rights reserved.

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