Advanced Waste Monitoring: Field Trials of a Wireless Sensor Network for Radioactive Waste Package Integrity Assessment

Abstract Radioactive waste materials, produced from nuclear technologies and power generation, must be safely contained and confined into suitable packaging systems that align with international global standards for disposal. One of the most important aspects related to package disposal is the possibility to monitor and control the physical and thermo-mechanical properties of the overall waste form over time. With recent technological advancements, there is now the capability to deploy flexible and distributed wireless sensor networks for long-term monitoring, diminishing reliance on intricate cabling infrastructure or mechanical scanning systems. This approach can substantially reduce inconsistencies and human errors that typically arise during the information management of packages throughout the disposal process, and integrating these technologies with decommissioning machinery, such as conveyor belts, robotic arms, and specific demolition equipment, may provide real-time radiation data during all stages of the decommissioning process. This study focused on validating and testing a novel system for identifying and continuously monitoring the integrity of stored radioactive waste packages developed at the University of Pisa. It is based on a network of wireless node devices equipped with solid-state, micro-power radiation detectors. Preliminary field trials were conducted at the Nucleco storage site in Rome, demonstrating the system’s efficiency in providing detailed insights into the activity distribution within cemented overpacks and the system’s ability to transmit data correctly even in harsh environmental conditions. Further, a joint demonstration test at ÚJV Řež, in line with the objectives of the H2020 European Project PREDIS, was conducted to emphasize the system’s ability to offer a comprehensive waste monitoring solution. The system’s novel ability to infer package deterioration and degradation based on activity data in a completely automated way sets it apart from existing methods, marking a significant advancement in destructive and non-destructive testing techniques.