Project
A Nuclear Verification and Disarmament Laboratory
Nuclear weapons pose a grave threat not only to individual nations but to humanity as a whole, with nine countries possessing a total of some 12,700 nuclear weapons. Nuclear disarmament is a shared global interest, but the international community remains divided on how to achieve it. There is, however, a broad consensus that the process needs to be carried out in a transparent and reliable manner, which requires robust verification mechanisms. The project A Nuclear Verification and Disarmament Laboratory studies such verification mechanisms with simulation-based approaches. The research focuses on two verification concepts that rely heavily on numerical simulations in their methods. The first concept is nuclear archaeology, which serves to ensure verifiable fissile material accounting by supporting the reconstruction of the operating history of fissile material production facilities. The second concept is warhead authentication with gamma spectroscopy, which is a technique to ensure the authenticity of a nuclear warhead that is to be dismantled without revealing details that a state may consider confidential. The research is structured in three subprojects: Nuclear Archaeology with Reprocessing Waste, Isotope Ratio Method, and Warhead Authentication.
Project Details
Project term
August 1, 2023–October 31, 2024
Affiliations
RWTH Aachen University
TU Darmstadt
Institute
Robust Data Science
Project Manager
Principal Investigator
Methods
Nuclear Archaeology with Reprocessing Waste
This sub-project sought to advance the development of a Bayesian inference frameworkfor analyzing the isotopic composition of reprocessing waste to verify the operating history of nuclear reactors. In reporting period, we improved existing and developed new algorithms for optimizing the performance of the framework by selecting suitable isotopic ratios to use as observable variables. In a simulated case study, we applied the framework to a computational model of the 5MWe reactor at Yongbyon, North Korea (Democratic People’s Republic of Korea), since this reactor’s plutonium production history relevant for potential future disarmament agreements with North Korea. We found that the Bayesian inference framework is in, principle, suitable for reconstructing the operational history of the 5MWe reactor at Yongbyon. Using all of the available information as prior knowledge, the reconstruction does not directly yield more information on individual inference variables, nevertheless, a more precise final plutonium estimate can be obtained. In a potential scenario where inspectors could visit the Yongbyong site, the available prior information could be wrong. Analyzing this case by using wrong prior limits, we were able to show that there is potential to detect false assumptions or declarations about prior information. These results demonstrate the potential for this novel method to support the verification of fissile material stockpile accounts.
Isotope Ratio Method
As part of the sub-project on the Isotope Ratio Method investigations into two different reactor designs were performed. Work with the British Trawsyfynydd II reactor has been concluded. Based on a dataset of simulated hypothetical operational histories, previously created under this project, surrogate models for relevant isotopic ratios within the moderator graphite were created using Gaussian Process Regression. Reconstructions of sample operational histories using Bayesian Inference were then performed and the results studied. For our final application we simulated the irradiation histories of real graphite samples taken during a historic sampling campaign. We were then able to successfully reconstruct said histories based on the predicted isotopic data. Additionally, a model of the German ”Forschungsreaktor 2” has been implemented, and initial simulations were performed to study the irradiation of steel plugs within the reactor. The results did however not prove promising for inverse analysis, and thus no extensive study was conducted.
Warhead Authentication
The goal of this sub-project was to study the vulnerability of current measurement systems to cheating and to investigate options for making the systems more robust. First, we developed a new pulse-height tally for the open source Monte Carlo neutron and photon transport software OpenMC to enable accurate simulations of the γ spectra. Then, we explored cheating scenarios in warhead confirmation processes, using simulations to model emissions, detector response matrices, and scenarios involving the substitution of plutonium or the entire weapon with alternative radioactive sources. We demonstrated that the measurement systems used for such verification tasks in the past can potentially be fooled by carefully constructed hoax objects. Third, we developed a genetic algorithm for optimizing binning structures in low-resolution gamma spectroscopy for warhead verification. By optimizing the binning structure, the potential to fool the detection systems can be reduced.
Additional Project Information
DFG classification: 309 Particles, Nuclei and Fields
Software: Serpent 2, OpenMC, Onix, PyMC
Cluster: CLAIX
Publications
Fichtlscherer, Christopher and Miah, Milon and Frieß, Friederike and Göttsche,
Malte and Kütt, Moritz. ”Modeling Gamma Detectors in OpenMC: Validation of
a Newly Implemented Pulse-Height Tally”. Progress in Nuclear Energy, July 2024.
doi:10.1016/j.pnucene.2024.105186
Fichtlscherer, Christopher and Kütt, Moritz. ”Uniqueness, Reproducibility and
Discrimination of Nuclear Warhead Gamma Signatures”. Science & Global Security.
October 2024. doi:10.1080/08929882.2024.2387966
Jung, Benjamin, Figueroa Caceres, Antonio and Göttsche, Malte. ”Towards inferring
reactor operations from high-level waste”. Nuclear Engineering and Technology,
February 2024. doi:10.1016/j.net.2024.02.031
J. Konrad, ”Reconstructing Plutonium and Tritium Production Modes with Nuclear
Archaeology. A First Implementation”, Bachelor’s thesis at RWTH Aachen,
September 2023.
J. Bosse, ”Applying Bayesian Inference-Based Nuclear Archaeology to a Simulated
Case Study of DPRK”, Master’s Thesis at RWTH Aachen, June 2024.
F. Unruh, ”Applying neural networks in nuclear archaeology with spent nuclear
fuel”, Master’s Thesis, RWTH Aachen at October 2023.