Radiation Hardened robotics for remote INspectiOn - RHINO
Lead Research Organisation:
Lancaster University
Department Name: Engineering
Abstract
In March 2011 a magnitude-9.0 earthquake struck in the Pacific Ocean off the northeast coast of Japan's Honshu island. Named the Great East Japan Earthquake by the Japanese government, it triggered a massive tsunami that flooded more than 200 square miles of coastal land. This devastating disaster caused a series of catastrophic failures resulting in the meltdown of the Fukushima Daiichi Nuclear Power Plant (NPP) and initiated a nuclear emergency. Reactor meltdown occurs when the cooling systems used to maintain and control the temperature of the nuclear fuel fails. The fuel then heats up uncontrollably and breaches the containment vessel or creates enough pressure to cause an explosion. Reactor meltdown occurred at all three reactors at Fukushima, resulting in fuel debris being dispersed throughout the reactors.
Retrieval of the fuel debris from the Fukushima Daiichi NPP is of great importance for decommissioning and waste management. It requires detailed understanding of the radioisotope composition within the debris and knowledge of their location. However, inside the stricken reactors' containment vessels, the radiation levels are so intense it presents a significant challenge. It prevents direct human intervention, can overwhelm detectors and sensors, damage electronics and cause materials to perish. Access routes to inside the containment vessels are also very narrow. To make general observations, identify fuel debris composition, location and retrieval, dedicated robots are deployed. Many of the robots deployed to date have failed due to radiation damage during operation or their function is severely hampered by the extreme environment.
This project brings together two world-leading research activities in the United Kingdom associated with radiation-hard, portable radiation detection (Lancaster University) and the development of small, radiation-hard remotely-operated vehicles (The University of Manchester) in collaboration with Okayama University and Kobe City College of Technology who have pioneered radiation-hard processors. The key aim of the research is to develop and deploy a simplified robot that prioritises radiation hardness and reliability over functional complexity. The hypothesis is, 'can such robots be more effective than the sophisticated alternatives tried to date?'. The ground-based radiation-hard robot will be equipped with non-destructive sensors for remote inspection. A radiation tolerant payload consisting of radiation sensors and LiDAR (light detection and ranging) will afford 3-dimensional (3D) spatial mapping of highly radioactive environments superimposed with located radiation intensities and radioisotope identities. The robot will be tested in realistic fields to demonstrate its ability to locate and identify dispersed radioisotopes derived from nuclear fuel debris inside Fukushima's stricken reactors. Such technology is also applicable to the UK's nuclear decommissioning challenges, specifically at Sellafield Site Ltd., and world-leading research in fusion energy at the UK Atomic Energy Authority.
Retrieval of the fuel debris from the Fukushima Daiichi NPP is of great importance for decommissioning and waste management. It requires detailed understanding of the radioisotope composition within the debris and knowledge of their location. However, inside the stricken reactors' containment vessels, the radiation levels are so intense it presents a significant challenge. It prevents direct human intervention, can overwhelm detectors and sensors, damage electronics and cause materials to perish. Access routes to inside the containment vessels are also very narrow. To make general observations, identify fuel debris composition, location and retrieval, dedicated robots are deployed. Many of the robots deployed to date have failed due to radiation damage during operation or their function is severely hampered by the extreme environment.
This project brings together two world-leading research activities in the United Kingdom associated with radiation-hard, portable radiation detection (Lancaster University) and the development of small, radiation-hard remotely-operated vehicles (The University of Manchester) in collaboration with Okayama University and Kobe City College of Technology who have pioneered radiation-hard processors. The key aim of the research is to develop and deploy a simplified robot that prioritises radiation hardness and reliability over functional complexity. The hypothesis is, 'can such robots be more effective than the sophisticated alternatives tried to date?'. The ground-based radiation-hard robot will be equipped with non-destructive sensors for remote inspection. A radiation tolerant payload consisting of radiation sensors and LiDAR (light detection and ranging) will afford 3-dimensional (3D) spatial mapping of highly radioactive environments superimposed with located radiation intensities and radioisotope identities. The robot will be tested in realistic fields to demonstrate its ability to locate and identify dispersed radioisotopes derived from nuclear fuel debris inside Fukushima's stricken reactors. Such technology is also applicable to the UK's nuclear decommissioning challenges, specifically at Sellafield Site Ltd., and world-leading research in fusion energy at the UK Atomic Energy Authority.
Publications
Alrawash S
(2024)
Prediction of Fuel Debris Location in Fukushima Nuclear Power Plant using Machine Learning
in EPJ Web of Conferences
| Description | We have: 1. Evaluated the radiation hardness of a selection of essential hardware components to build a basic radiation-hard land-based robotic platform. 2. Developed machine learning algorithms for composition identification and localisation of materials in a high radiation environment using data from a diamond detector. 3. Constructed and partially demonstrated a basic radiation hard robotic platform. 4. Advanced tools for the configuration of our Japanese collaborator's radiation hardened Field Programmable Gate Array (FPGA). |
| Exploitation Route | 1. Application deployment of rad-hard FPGAs and robotic components such as motors, encoders, power transistors and LiDAR (Light Detection and Ranging). 2. Advances in machine learning for material identification and composition for other application areas. |
| Sectors | Aerospace Defence and Marine Electronics Energy |
| Description | Dalton Cumbria Facility (DCF) knowledge exchange and joint grant submission |
| Organisation | Dalton Cumbria Facility |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Knowledge exchange and satellite grant proposal preparation. |
| Collaborator Contribution | Identification of funding scheme and knowledge contribution to grant proposal. |
| Impact | Submitted grant proposal. |
| Start Year | 2024 |
| Description | Mirion Technologies (Canberra UK) Ltd. knowledge and facilities partnership |
| Organisation | Mirion Technologies Inc |
| Department | Mirion Technologies (Canberra UK) Limited |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | The research team demonstrated operation of their diamond detector and shared data. |
| Collaborator Contribution | The partner (Mirion Technologies Ltd.) provided access to their Warrington facilities and radioactive sources for testing of our diamond detector. |
| Impact | 1. Identification of cabling faults and corrective action. 2. Confirmed operation of diamond detector and data acquisition chain in preparation for scheduled experiments using the ISIS Neutron and Muon Source. 3. High sample rate (8 GS/s) waveform data of diamond detector signals originating from an Am-241 alpha source. |
| Start Year | 2024 |
