Date of Award

3-23-2017

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Aeronautics and Astronautics

First Advisor

Anthony N. Palazotto, PhD.

Abstract

Generation of residual stress is an essential step in the generation of Goodman data via Air Force Research Laboratory's vibration-based fatigue test. Conventional Goodman data is constructed through uniaxial fatigue testing at a rate of 40 Hz, while the vibration-based testing excites stresses at 1,600 Hz in a stress state that is similar to those seen in gas turbine engine airfoils. A pre-strain procedure is conducted to form residual tensile stress, which serves as a steady stress when the specimen is subjected to fully-reversed vibration-based fatigue loads. This steady tensile stress is desired at the fatigue zone of the test article, but is the result of an adjacent compressive region in equilibrium, and as such, a FEM is necessary to determine the stress distribution throughout the entire sample. The goal of this work is to improve the FEM analysis associated with the pre-strain method for better accuracy of steady stress generation for Goodman data fatigue assessment. Improvements were made to the FEM by more effectively incorporating empirical tensile stress-strain behavior, in addition to more accurately representing the pressures and forces acting on the specimen during monotonic loading. Validations of improvements to the pre-strain steady stress generation procedure will be demonstrated on Aluminum 6061-T6 by comparing strain field results from digital image correlation to FEM analysis. The converged quasi-static FEM solution had a standard deviation in epsilon yy of 2,557 microstrain and predicted a residual sigma yy of 10.72 ksi, while the optimized time-dependent solution had a standard deviation in epsilon yy of 308.9 microstrain (less than the experimental variation of 376.1 microstrain) and predicted a residual sigma yy of 4.93 ksi. The increased accuracy of these models altered residual stresses on a Goodman line by as much as 26 compared with past results.

AFIT Designator

AFIT-ENY-MS-17-M-269

DTIC Accession Number

AD1055346

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