PhD Defense by Adrienne Muth

Event Details
  • Date/Time:
    • Friday April 9, 2021
      12:00 pm - 2:00 pm
  • Location: Atlanta, GA; REMOTE
  • Phone:
  • URL: Bluejeans
  • Email:
  • Fee(s):
    N/A
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Summaries

Summary Sentence: A Large Scale Computational Study of Fatigue Hot-spots

Full Summary: No summary paragraph submitted.

THE SCHOOL OF MATERIALS SCIENCE AND ENGINEERING

GEORGIA INSTITUTE OF TECHNOLOGY

Under the provisions of the regulations for the degree

DOCTOR OF PHILOSOPHY

on Friday, April 9, 2021
12:00 PM
 

via 

  

BlueJeans Video Conferencing 

https://bluejeans.com/396605134


will be held the

DISSERTATION DEFENSE


for


Adrienne Muth

"A Large Scale Computational Study of Fatigue Hot-spots"

Committee Members:
 

 

Prof. David McDowell Advisor, ME/MSE

Prof. Surya Kalidindi ME/MSE/CSE

Prof. Richard Neu ME/MSE

Reji John, Ph.D., AF Research Lab, Materials and Manufacturing Directorate

Adam Pilchak, Ph.D., AF Research Lab, Materials and Manufacturing Directorate


Abstract: 

 

Formation of a fatigue crack at the subgrain scale is a statistically rare event, as plastic deformation at the microscale ranges from highly heterogeneous at low strain to homogeneous at high strain. Fatigue Indicator Parameters (FIPs) for Ti-6Al-4V are computed using crystal plasticity finite element modeling of uniaxial cyclic straining of ensembles of statistical volume elements for a range of distinct microstructures at several strain amplitudes and mean strain conditions.  The selection of FIPs is informed by prior experimental studies. The sites of extreme value (EV) FIPs that are most likely to form and grow a fatigue crack are identified in these simulations, and 2-point spatial correlations are applied to investigate the higher dimensional influence of microstructure attributes in the neighborhood of these fatigue hot-spots. To reduce the high dimensionality of the associated 2-point correlations, principal component analysis is applied.  A reduced-order model using an artificial neural network is used to classify EV FIP locations based on these neighborhood spatial correlations.

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Graduate Studies

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Keywords
Phd Defense
Status
  • Created By: Tatianna Richardson
  • Workflow Status: Published
  • Created On: Mar 29, 2021 - 1:16pm
  • Last Updated: Mar 29, 2021 - 1:16pm