Simulated Microstructure-Sensitive Extreme Value Probabilities for High Cycle Fatigue of Duplex Ti-6Al-4V

Abstract

A newly developed microstructure-sensitive extreme value probabilistic framework for fatigue variability based on computational polycrystal plasticity is exercised to compare the driving forces for fatigue crack formation (nucleation and early growth) at room temperature for four different microstructure variants of duplex a Ti-alloy. The aforementioned probabilistic framework links certain extreme value fatigue response parameters with microstructure attributes at fatigue critical sites through use of marked correlation functions. By applying this framework to study the driving forces for fatigue crack formation in these microstructure variants of Ti-4V, these microstructures can be ranked in terms of relative high cycle fatigue (HCF) performance and the correlated microstructure attributes that have the most influence on the predicted fatigue response can be identified. Nonlocal fatigue indicator parameters (FIPs) based on the cyclic plastic strain averaged over domains on the length scale of the microstructure attributes (e.g. grains, phases) are used to estimate the driving force(s) for fatigue crack formation are estimated using these FIPs.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2010
Accession Number
ADA523967

Entities

People

  • Craig Przybyla
  • David L. Mcdowell

Organizations

  • Georgia Tech

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Air Force Research Laboratories
  • Bulk Materials
  • Engineering
  • Grain Size
  • Materials
  • Materials Science
  • Mechanical Engineering
  • Microstructure
  • Military Research
  • Particle Size
  • Plastic Properties
  • Probability
  • Probability Distributions
  • Random Variables
  • Simulations

Fields of Study

  • Materials science

Readers

  • Computational Fluid Dynamics (CFD)
  • Powder metallurgy of Titanium alloys.
  • Structural Health Monitoring of Composite Structures.