Fragmentation Modeling Using the Expectation Maximization Algorithm

Abstract

The modeling of fractures typically uses the Poisson distribution to select the number of particles resulting from a fracture of a solid body. This applies to bullets when striking a plate. This report develops a method to model the number of subparticles using a mixture of Poisson distributions. The goal is to find the mixture with the smallest number of components that fits the data. Rather than attempting to find the distribution of lambda, it is assumed the values of lambda are clustered and the centroids of these clusters constitute a useful model.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2011
Accession Number
ADA550631

Entities

People

  • Andrew A. Thompson

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Bodies
  • Data Sets
  • Department Of Defense
  • Distribution Functions
  • Equations
  • Fragmentation
  • Maximum Likelihood Estimation
  • Military Research
  • New York
  • Normal Distribution
  • Observation
  • Particles
  • Physical Properties
  • Probability
  • Probability Distributions
  • Solid Bodies

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Educational Psychology
  • Statistical inference.