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Microstructure-Sensitive Models for Predicting Surface Residual Stress Redistribution in P/M Nickel-Base Superalloys

Burba, Micheal Eric
http://rave.ohiolink.edu/etdc/view?acc_num=dayton1492532628147262

Abstract Details

2017, Doctor of Philosophy (Ph.D.), University of Dayton, Materials Engineering.
Compressive surface residual stresses achieved by mechanical surface treatments (shot peening, low-plasticity burnishing, or laser shock peening) typically extend component life under fatigue loading. Designers are unable to include this surface residual stress benefit in design life predictions due to the absence of detailed and accurate models of the behavior, and to the uncertainty of residual stress profiles that exist both before and after service. Generalization of coupled creep-plasticity models to incorporate microstructural features, size distributions, and volume fractions can provide an analytical description of the relevant relaxation mechanisms, allowing engineered residual stress to be taken into account in design. The current study combines observations from microstructural characterization and mechanical testing with the development of numerical models to predict surface residual stress relaxation following exposure to load and temperature. The grain size and γ' precipitate distributions are quantified for two different IN100 microstructures, and experimental measurements of the yield strength and creep behavior of the materials are obtained. The microstructural data are incorporated into a coupled creep-plasticity modeling framework which describes how the prior plastic deformation affects creep response. Residual stress relaxation predictions are validated against measured residual stress profiles from shot-peened laboratory scale experiments for both heat treatments of IN100 under service-relevant conditions. The resulting numerical model accurately predicts relaxation of engineered residual stresses under expected service conditions, using only data from standard mechanical tests and microstructural characterization methods, thereby enabling favorable residual stresses to be considered in the design process.
Robert Brockman, Ph.D. (Advisor)
Dennis Buchanan, Ph.D. (Committee Member)
Paul Murray, Ph.D. (Committee Member)
Michael Caton, Ph.D. (Committee Member)
Reji John, Ph.D. (Committee Member)
194 p.
Materials Science
nickel-base superalloy; residual stress; gamma prime precipitates; x-ray diffraction; hole drilling; x-ray elastic constant; shot peening

Recommended Citations

Citations

  • Burba, M. E. (2017). Microstructure-Sensitive Models for Predicting Surface Residual Stress Redistribution in P/M Nickel-Base Superalloys [Doctoral dissertation, University of Dayton]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1492532628147262

    APA Style (7th edition)

  • Burba, Micheal. Microstructure-Sensitive Models for Predicting Surface Residual Stress Redistribution in P/M Nickel-Base Superalloys. 2017. University of Dayton, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=dayton1492532628147262.

    MLA Style (8th edition)

  • Burba, Micheal. "Microstructure-Sensitive Models for Predicting Surface Residual Stress Redistribution in P/M Nickel-Base Superalloys." Doctoral dissertation, University of Dayton, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1492532628147262

    Chicago Manual of Style (17th edition)

dayton1492532628147262
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© 2017, all rights reserved.
This open access ETD is published by University of Dayton and OhioLINK.