PI3SO: A Spectroscopic γ-Ray Scanner Table for Sort and Segregate Radwaste Analysis

Author:

Poma Gaetano Elio1ORCID,Failla Chiara Rita1ORCID,Amaducci Simone1ORCID,Cosentino Luigi1ORCID,Longhitano Fabio2ORCID,Vecchio Gianfranco1ORCID,Finocchiaro Paolo1ORCID

Affiliation:

1. INFN Laboratori Nazionali del Sud, 95123 Catania, Italy

2. INFN Sezione di Catania, 95123 Catania, Italy

Abstract

The current scenario of radioactive waste management requires innovative and automated solutions to ensure its effectiveness and safety. In response to this need, the Proximity Imaging System for Sort and Segregate Operations (PI3SO) project was proposed. It is a gamma radiation proximity scanner system for radioactive waste with the primary goal of speeding up some aspects of the waste management cycle while reducing direct human operations. The system will provide proximity imaging for hot-spot finding and spectral analysis for radiological characterization, enabling semiautomatic recognition, sorting and separation of radioactive waste. The core of the proposed scanning system consists of an array of 128 CsI(Tl) scintillators, 1 cm3 size, coupled with silicon photomultipliers (SiPMs), installed on a motorized bridge sliding along a suitable table in order to scan the materials under investigation.

Funder

INFN-Energy committee

Publisher

MDPI AG

Reference34 articles.

1. (2024, July 19). Decommissioning of Nuclear Installations. Available online: https://www.iaea.org/topics/decommissioning.

2. International Atomic Energy Agency (1994). Status of Technology for Volume Reduction and Treatment of Low and Intermediate Level Solid Radioactive Waste, IAEA.

3. International Atomic Energy Agency (2022). Status and Trends in Spent Fuel and Radioactive Waste Management, IAEA. No. NW-T-1.14 (Rev. 1).

4. Donovan, J. (2024, July 19). Robots, AI and 3D Models: How High-Tech Breakthroughs Help Nuclear Decommissioning. Available online: https://www.iaea.org/bulletin/robots-ai-and-3d-models-how-high-tech-breakthroughs-help-nuclear-decommissioning.

5. Monk, S.D., West, C., Bandala, M., Dixon, N., Montazeri, A., Taylor, C.J., and Cheneler, D. (2021). A Low-Cost and Semi-Autonomous Robotic Scanning System for Characterising Radiological Waste. Robotics, 10.

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