Novel Methods for Rapid, Reliable, and Rigorous Analysis of Gamma-ray Spectra Using Optimization and Nuclide Modeling

Abstract

Gamma-ray spectroscopy is a powerful, field-deployable nondestructive analysis technique that may be used for rapid analysis of fission products in post-detonation fallout debris; however, the analysis of complex gamma-ray spectrum data presents a number of difficulties. These challenges include nuclide identification coupled with spectral interference removal, decay chain activity calculation, correction for self-attenuation, and treatment of uncertainty. This research will develop and implement mathematical methods for spectrum analysis using nuclide buildup and decay modeling, convex optimization, and Bayesian statistics. The analysis engine we develop will automatically identify gamma-emitting radionuclides within the sample, resolve interferences, and simultaneously calculate activities of entire decay chains in a single analytic step. This research will increase the quality of post-detonation response technology by minimizing variance among analysts and increase confidence in results, apply a rigorous statistical treatment of all uncertainties, and give a complete report of results include probability distributions, covariances, mean values, and standard uncertainties. The project is divided into two phases over the course of three years. Phase I will focus on the development of the algorithms and subroutines for the new approach to spectrum analysis as well as the design and collection of spectral data that will span a range of detector types and measurement parameters expected in post-detonation response scenarios and standard gamma-ray spectrum analysis capabilities. Phase II will focus on the analysis of the test datasets using the new methodology as well as traditionally employed techniques as a basis for comparison.

Document Details

Document Type
DoD Grant Award
Publication Date
May 26, 2016
Source ID
HDTRA11610037

Entities

People

  • Steven Biegalski

Organizations

  • Defense Threat Reduction Agency
  • University of Texas at Austin

Tags

Fields of Study

  • Physics

Readers

  • Nuclear and Radiation Engineering.
  • Regression Analysis.
  • Solar Physics

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference