Accession Number:

ADA446159

Title:

Quantitative Object Reconstruction using Abel Transform Tomography and Mixed Variable Optimization

Descriptive Note:

Master's thesis

Corporate Author:

AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH

Personal Author(s):

Report Date:

2006-03-01

Pagination or Media Count:

97.0

Abstract:

Researchers at the Los Alamos National Laboratory LANL are interested in quantitatively reconstructing an object using Abel transform x-ray tomography. Specifically, they obtain a radiograph by x-raying an object and attempt to quantitatively determine the number and types of materials and the thickness of each material layer. Their current methodologies either fail to provide a quantitative description of the object or are generally too slow to be useful in practice. As an alternative, the problem is model here as a mixed variable programming MVP problem, in which some variables are nonnumeric and for which no derivative information is available. The generalized pattern search GPS algorithm for linearly constrained MVP problems is applied to the x-ray tomography problem, by means of the NOMADm MATLAB software package. Numerical results are provided for several test configurations of cylindrically symmetrical objects and show that, while there are difficulties to be overcome by researchers at LANL, this method is promising for solving x-ray tomography object reconstruction problems in practice.

Subject Categories:

  • Computer Programming and Software
  • Nuclear Physics and Elementary Particle Physics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE