| Issue |
EPJ Web Conf.
Volume 239, 2020
ND 2019: International Conference on Nuclear Data for Science and Technology
|
|
|---|---|---|
| Article Number | 17005 | |
| Number of page(s) | 5 | |
| Section | Experimental Facilities, Equipment, Techniques and Methods | |
| DOI | https://doi.org/10.1051/epjconf/202023917005 | |
| Published online | 30 September 2020 | |
https://doi.org/10.1051/epjconf/202023917005
Utilizing nuclear data in delayed gamma-ray spectroscopy inverse Monte Carlo analysis
1 Integrated Support Center for Nuclear Nonproliferation and Nuclear Security, Japan Atomic Energy Agency, 2-4 Shirane Shirakata, Tokai-mura, Ibaraki, Japan
2 Nuclear Security Unit, Joint Research Centre, Via E. Fermi 2749, I-21027 Ispra (VA), ITALY
* e-mail: rodriguez.douglaschase@jaea.go.jp
Published online: 30 September 2020
Safeguards verification of uranium and plutonium in high-radioactivity nuclear material is currently performed using destructive analysis techniques. However, the preparation method is a burden on both the safeguards inspectors and facility operators. While nondestructive assay (NDA) techniques would improve the efficiency and time, there are no passive NDA techniques available to directly verify the U and Pu content. As an alternative, the JAEA and JRC are collaboratively developing the Delayed Gamma-ray Spectroscopy (DGS) active-interrogation NDA technique to evaluate the fissile composition from the unique fission product yield distributions. To analyze the data we are developing an Inverse Monte Carlo (IMC) method that simulates the interrogation and evaluates the individual contributions from the mixed nuclear material to the composite spectrum. While the current nuclear data affects the ability to evaluate the composition, the IMC analysis method can be used to determine the systematic uncertainty contributions and has the potential to improve the nuclear data. We will present the current status of the DGS collaborative work as it relates to the development of the DGS IMC analysis.
© The Authors, published by EDP Sciences, 2020
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