Statistical Analysis of Metallurgical Mechanical Properties with an Application to Ti-6Al-4V Alloy Fatigue Data.

Abstract

The potential application of statistical methods to metallurgical practices was shown using an example of titanium alloy fatigue data. Materials Laboratory, AFWAL was interested to see (1) whether more meaningful S-N curves could be drawn using statistical methods, (2) which of the data can be identified as outliners, and (3) how the different treatments of the alloy compare. Best-fit curves were determined for each treatments by linear and nonlinear regression analysis. Residual analysis was used to test the assumptions on the random error and to select extreme values for further analysis. Seven of the nine extreme values found did not lie within ninety-nine percent prediction intervals determined about the fitted line and were classified as outliers to be fractographically examined by Materials Laboratory. Regression results of sets of treatments, hypothesized by Materials Laboratory to be drawn from similar populations, were compared to determine whether the treatments within a set agree with the Materials Laboratory's hypothesis. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1981
Accession Number
ADA110727

Entities

People

  • Gary A. Killian

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Biomedical
  • Ground and Sea Platforms
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Aircraft Equipment
  • Aircraft Industry
  • Aircrafts
  • Crystal Structure
  • Heat Treatment
  • Information Science
  • Materials
  • Materials Engineering
  • Materials Laboratories
  • Materials Science
  • Mechanical Properties
  • Mechanical Working
  • Modulus Of Elasticity
  • Regression Analysis
  • Statistical Analysis
  • Tensile Strength

Readers

  • Metallurgy
  • Regression Analysis.