A computer-vision aided Compton-imaging system for radioactive waste characterization and decommissioning of nuclear power plants

TL;DR

This paper presents a portable, cost-effective Compton camera system enhanced with computer vision and advanced algorithms for efficient radioactive waste detection, visualization, and 3D tomography, demonstrating promising results in nuclear waste management.

Contribution

The study introduces a high-performance, portable Compton imaging system with integrated computer vision and reconstruction algorithms, achieving TRL7 readiness for nuclear waste characterization.

Findings

Good image resolution and reduced measurement time.

Successful field tests at a nuclear waste disposal site.

Feasibility of 3D tomography from short measurements.

Abstract

Nuclear energy production is inherently tied to the management and disposal of radioactive waste. Enhancing classification and monitoring tools is therefore crucial, with significant socioeconomic implications. This paper reports on the applicability and performance of a high-efficiency, cost-effective and portable Compton camera for detecting and visualizing low- and medium-level radioactive waste from the decommissioning and regular operation of nuclear power plants. The results demonstrate the good performance of Compton imaging for this type of application, both in terms of image resolution and reduced measuring time. A technical readiness level of TRL7 has been thus achieved with this system prototype, as demonstrated with dedicated field measurements carried out at the radioactive-waste disposal plant of El Cabril (Spain) utilizing a pluarility of radioactive-waste drums from decomissioned nuclear power plants. The performance of the system has been enhanced by means of computer-vision techniques in combination with advanced Compton-image reconstruction algorithms based on Maximum-Likelihood Expectation Maximization. Finally, we also show the feasibility of 3D tomographic reconstruction from a series of relatively short measurements around the objects of interest. The potential of this imaging system to enhance nuclear waste management makes it a promising innovation for the nuclear industry.