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Connecting Computed-Tomography-Assisted Discontinuity Detection in Ni-Base Superalloys to Engineering Simulation

[+] Author Affiliations
Adrian Loghin, Al Cerrone, Anjali Singhal, Ying Zhou

GE Global Research, Niskayuna, NY

Paper No. GT2017-65087, pp. V07AT31A017; 7 pages
doi:10.1115/GT2017-65087
From:
  • ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition
  • Volume 7A: Structures and Dynamics
  • Charlotte, North Carolina, USA, June 26–30, 2017
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 978-0-7918-5092-3
  • Copyright © 2017 by ASME

abstract

The impact of non-metallic inclusions on fatigue life of various materials (steel alloys, Ni-base) has been studied extensively for more than fifty years. Specimen test procedures at various conditions (temperature, air or vacuum, LCF, HCF, VHCF) have been used to quantify the impact of inherent manufacturing induced discontinuities (ceramic inclusions, pores, carbides) on the fatigue capability of the material. Frequently, the fatigue data shows large scatter, leading to a large set of test specimens that has to be considered to quantify the lower tail of the fatigue life distribution. To understand the specimen recorded fatigue lives, assessment of the discontinuity population is usually conducted post-mortem by fractography wherein the origin of crack nucleation, size of the eventual inclusion on fracture surface, and distance from the free surface are identified.

3D characterization techniques can be leveraged to extract previously unobtainable information out of the testing specimens non-destructively. In this study, samples of different Powder Metallurgy (PM) Ni-base superalloys with different inclusion content and size were scanned to identify the Computed Tomography (CT) test setup that would provide adequate contrast to discriminate between matrix and eventual discontinuities (inclusions, pores). To further validate the capability to identify discontinuities within the matrix (Ni base alloy) using the CT technique, a set of LCF specimens were scanned prior to the test procedure. Post-failure fractography analysis showed that one of the CT indications is correlated with the failure-inducing inclusion.

Volume reconstruction and finite element meshing conclude this study to: a) further provide a size distribution of inclusions in the scanned volume as well as location of these inclusions relative to the surface of the specimen and b) connect direct measurement with engineering simulation.

Copyright © 2017 by ASME

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