Development of Methods to Observe Material's Fatigue and Corrosion Damage through Surface Characteristics Monitoring

Abstract

White Light Interferometry was used for surface characterization accompanied by other methods to observe materials damage caused by corrosion and fatigue. White Light Interferometry has a spatial resolution of 0.2 micrometer and depth resolution of 3 nm. It was applied to study corroded surfaces. Parameters such as average roughness and pit depths were determined. The results provided the details of the critical pit size that can lead to fatigue crack initiation in Al-2024-T3. A relationship between the critical pit depth and the stress intensity factor, a structural integrity parameter, was determined. In the second part of this report, a method to characterize the depression zone at a crack tip and predict upcoming fracture under static load using white light interference microscopy was developed and studied. Results showed an exponential relationship between the area of the crack tip deformation and volume of the crack tip depression with the stress applied to the pre-cracked sample. The findings of this study indicate that it is possible to determine a critical rate of change in surface deformation at a crack tip versus the applied stress that can be used to predict oncoming catastrophic failure.

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Document Details

Document Type
Technical Report
Publication Date
Aug 31, 2000
Accession Number
ADA382093

Entities

People

  • Jody L. Schroeder
  • Laura B. Simon

Organizations

  • University of Dayton

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Corrosion
  • Corrosion Resistance
  • Crack Tips
  • Electron Microscopy
  • Fracture (Mechanics)
  • Geometric Forms
  • Interferometry
  • Lines (Geometry)
  • Materials
  • Mechanics
  • Microscopy
  • Scanning Electron Microscopy
  • Structural Integrity
  • Three Dimensional
  • Two Dimensional

Readers

  • Computational Modeling and Simulation
  • Materials Science (Mechanical Engineering).
  • Vision Science/Vision Psychology/Cognitive Neuroscience.