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Title: Fission Gamma-Ray Spectra Relevant to Post-Detonation Debris Analysis

Abstract

A terrorist-generated nuclear attack would invoke unprecedented pressure for a rapid and accurate nuclear forensics characterization of the event. In-situ fission product gamma-ray spectroscopy offers the potential for a significant reduction in analysis time while still providing high fidelity identification of the primary composition of the detonated device. The in-situ spectroscopic approach we are proposing can rapidly identify the species that underwent fission as well as the fission-inducing neutron energy spectrum. To demonstrate this goal, we have used the gammaray history from our previously obtained LLNL-LANL-TUNL fission product-yield (FPY) data to provide insights for post-detonation debris analysis. The proposed method relies on the ratio of photopeak areas for selected gamma-rays representing the FPYs of sixteen fission products generated using mono-energetic neutrons at energies between 0.5 MeV to 14.8 MeV on highlyenriched 239Pu, 235U, and 238U sealed targets. In addition to the fission product ratio measurements we have applied a new regression analysis based on our experimental FPY data and validated the approach using relevant Godiva FPY data and (surrogate) photofission product yields of 240Pu. The main advantage of the regression analysis is that it investigates the FPY data set as a whole, rather than focusing on individual FPY ratios.

Authors:
 [1];  [1];  [2];  [2]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1491970
Report Number(s):
LLNL-TR-765862
955047
DOE Contract Number:  
AC52-07NA27344
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Citation Formats

Tonchev, Anton P., Silano, Jack, Wilhelmy, Jerry, and Gooden, Matthew. Fission Gamma-Ray Spectra Relevant to Post-Detonation Debris Analysis. United States: N. p., 2019. Web. doi:10.2172/1491970.
Tonchev, Anton P., Silano, Jack, Wilhelmy, Jerry, & Gooden, Matthew. Fission Gamma-Ray Spectra Relevant to Post-Detonation Debris Analysis. United States. doi:10.2172/1491970.
Tonchev, Anton P., Silano, Jack, Wilhelmy, Jerry, and Gooden, Matthew. Thu . "Fission Gamma-Ray Spectra Relevant to Post-Detonation Debris Analysis". United States. doi:10.2172/1491970. https://www.osti.gov/servlets/purl/1491970.
@article{osti_1491970,
title = {Fission Gamma-Ray Spectra Relevant to Post-Detonation Debris Analysis},
author = {Tonchev, Anton P. and Silano, Jack and Wilhelmy, Jerry and Gooden, Matthew},
abstractNote = {A terrorist-generated nuclear attack would invoke unprecedented pressure for a rapid and accurate nuclear forensics characterization of the event. In-situ fission product gamma-ray spectroscopy offers the potential for a significant reduction in analysis time while still providing high fidelity identification of the primary composition of the detonated device. The in-situ spectroscopic approach we are proposing can rapidly identify the species that underwent fission as well as the fission-inducing neutron energy spectrum. To demonstrate this goal, we have used the gammaray history from our previously obtained LLNL-LANL-TUNL fission product-yield (FPY) data to provide insights for post-detonation debris analysis. The proposed method relies on the ratio of photopeak areas for selected gamma-rays representing the FPYs of sixteen fission products generated using mono-energetic neutrons at energies between 0.5 MeV to 14.8 MeV on highlyenriched 239Pu, 235U, and 238U sealed targets. In addition to the fission product ratio measurements we have applied a new regression analysis based on our experimental FPY data and validated the approach using relevant Godiva FPY data and (surrogate) photofission product yields of 240Pu. The main advantage of the regression analysis is that it investigates the FPY data set as a whole, rather than focusing on individual FPY ratios.},
doi = {10.2172/1491970},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {1}
}