Development of Active Neutron NDA Techniques for Nonproliferation and Nuclear Security (5): Systematic Uncertainty and Preliminary Fission Yields From DGS Measurements Using an Inverse Monte Carlo Analysis

Year
2016
Author(s)
Hironobu Nakamura - Japan Atomic Energy Agency
Jun Takamine - Japan Atomic Energy Agency
M. Koizumi - Japan Atomic Energy Agency (JAEA)
M. Seya - Integrated Support Center for Nuclear Nonproliferation and Nuclear Security, JAEA
Douglas Chase Rodriguez - Integrated Support Center for Nuclear Security and Nuclear Nonproliferation, Japan Atomic Energy Agency
Fabiana Rossi - Integrated Support Center for Nuclear Security and Nuclear Nonproliferation, Japan Atomic Energy Agency
Abstract
Efficiently determining the composition of mixed nuclear materials (NM) is of significant inter- est for both safeguards and security. Addressing this need, a non-destructive analysis system using a pulsed DT neutron source is currently under development by researchers of the JAEA and the JRC (Ispra, Italy and Geel, Belgium). This collaboration plans to apply this system toward determining the Pu/U composition of purified MOX fuel and non-purified NM with high radioactivity (e.g. spent fuel, vitrified waste, melted fuel from reactor accidents, and next-generation fuel cycle materials). Of the techniques being incorporated into the system, the delayed gamma-ray spectroscopy (DGS) technique has the potential to establish fissionable material nuclide ratios to relatively high precision since each fissionable isotope has a unique fis- sion product yield. These fission products generate specific, time-dependent, gamma-ray energy spectra that extend well above 3 MeV, which is a benefit when applied to the NM of interest that have high passive gamma-ray emissions below this energy. The measured data will be analyzed by an Inverse Monte Carlo (IMC) method, which has the benefit of high-quality sys- tematic uncertainty determination through IMC analysis of Monte Carlo simulations utilizing the same foundational code. This presentation will describe the Monte Carlo (with systematic uncertainties calculations) and preliminary analysis results of measured data.