Experimental Resource Allocation for Statistical Simulation of Fretting Fatigue Problem (Preprint)

Abstract

Estimation of statistical moments from simulation, i.e., mean and standard deviation of an output, may involve large uncertainty caused by the variability in the input random variables. The allocation of resources to obtain more experimental data can reduce the variance of the output moments (mean and standard deviation). The methodology proposed and executed used an optimization method to determine the optimal number of additional experiments required to minimize the variance of the output moments given a constraint. A method to generate the output moments based on the moments of the input variables was implemented. The method used the multivariate t-distribution and the Wishart distribution to generate realizations of the population mean and population covariance of the input variables, respectively. This method was sufficient to handled independent and correlated variables. A fretting fatigue problem was explored to minimize the variance of cycles-to failure mean and standard deviation.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2012
Accession Number
ADA564357

Entities

People

  • Carolina Dubinsky
  • Gulshan Singh
  • Harry R. Millwater
  • Patrick Golden

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Bayesian Networks
  • Computational Science
  • Covariance
  • Data Science
  • Engineering
  • Experimental Data
  • Information Processing
  • Information Science
  • Mechanical Engineering
  • Particle Swarm Optimization
  • Probability
  • Random Variables
  • Simulations
  • Statistics

Readers

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