Statistical characterization of the geometric properties of particles in 7075‐T6 aluminium alloy

Abstract

Corrosion in aluminium alloys is initiated and sustained at constituent particles within the metal matrix via a localized galvanic process. These particles are also known to play a critical role in fatigue crack initiation and growth. Consequently, statistical characterization of particle geometrical features is critical when modelling corrosion and fatigue. A key statistic is particle size distribution, which was extensively modelled here via imaging of unstressed and fatigued 7075‐T6 aluminium alloys. Fatigued samples were obtained from the outer wing panels of teardown specimens from retired military aircraft. The purpose of this effort was therefore to analyse extensive sets of particle geometry data obtained via microscopy using advanced multimodal statistical modelling and to appropriately characterize the properties of constituent particles and fatigue cracks found in these specimens. The resulting distribution functions for the underlying modes are assumed to be three‐parameter Weibull distribution functions.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jun 18, 2014
Source ID
10.1111/ffe.12217

Entities

People

  • C. V. Haden
  • D. G. Harlow

Organizations

  • Defense Advanced Research Projects Agency
  • Lehigh University

Tags

Fields of Study

  • Materials science

Readers

  • Aerosol Science/Aerosol Physics
  • Neural Network Machine Learning.
  • Powder metallurgy of Titanium alloys.