Kreutle, M.FZJ* ; Niemeyer, I. (Researcher)FZJ* ; Aymanns, K. (Researcher)FZJ*

2025

Abstract: Member states of the Treaty on the Non-Proliferation of Nuclear Weapons that are not listed as nuclear weapons states are subject to international safeguards in order to ensure that no nuclear material is diverted or facilities are misused with the aim of building nuclear weapons. With that objective, the International Atomic Energy Agency (IAEA) and other safeguards authorities use technical measures such as seals, closed-circuit television (CCTV) cameras, radiation detectors or laser scanners in civil nuclear facilities. During the process of nuclear waste management, safeguards are applied in interim storage facilities and deep geological repositories to spent nuclear fuel, other nuclear waste forms, as well as casks and containers containing this material. These monitoring systems over the past have grown in complexity, produce large amounts of data and become more and more interconnected and automated. At the same time, digital twin concepts increasingly gain popularity in industry contexts while enabling technologies, e.g. high-performance computing and machine learning, become more easily available. This poster explores the topic of digital twins for safeguards in nuclear waste management by presenting models and software modules. At the core of our approach lies a monitoring system model implemented via a PostgreSQL database that incorporates data traces obtained from inspection data and facility operators’ declarations. To support interaction with the model, we provide a Python API that enables manipulation and tracking of the model state over time from an operator and an inspectorate perspective. Also presented here are the project’s continuous integration of tests, the automated deployment of its documentation, and its graphical user interface (GUI) which is implemented via a plotly-powered dash app. Beyond modeling, data storage and visualization, the presented software is capable of simulating different physical aspects such as neutron and gamma radiation as well as light detection and ranging (LiDAR) and it offers the possibility to generate synthetic data for compliance and diversion scenarios. The use of this synthetic data for the training of machine learning algorithms for experimental design optimization and anomaly detection is discussed. Finally, the poster will provide an outline of the envisioned scaling of this prototype software into a larger digital twin framework capable of processing and analyzing real measurement data can be alongside the synthetic data. The presented work aims at supporting and facilitating remote monitoring, the development of new safeguards techniques, as well as education and training, while aspiring to incorporate good practices of research software engineering.

Keyword(s): Nuclear waste management ; Digital twins ; Nuclear safeguards

1. Neu- und Weiterentwicklung von Konzepten, Methoden und Techniken für die internationale Kernmaterialüberwachung, insbesondere im Rahmen der nuklearen Entsorgung (SAFEGUARDS-3) (02W6279) (02W6279)
2. 1411 - Nuclear Waste Disposal (POF4-141) (POF4-141)