| Feb. 13, 2024, 4:19 p.m. |
Created
43
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[{"model": "core.projectfund", "pk": 61362, "fields": {"project": 9542, "organisation": 2, "amount": 504102, "start_date": "2022-11-01", "end_date": "2025-03-31", "raw_data": 179453}}]
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| Jan. 30, 2024, 4:24 p.m. |
Created
43
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[{"model": "core.projectfund", "pk": 54213, "fields": {"project": 9542, "organisation": 2, "amount": 504102, "start_date": "2022-11-01", "end_date": "2025-03-31", "raw_data": 156278}}]
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| Jan. 2, 2024, 4:15 p.m. |
Created
43
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[{"model": "core.projectfund", "pk": 47000, "fields": {"project": 9542, "organisation": 2, "amount": 504102, "start_date": "2022-11-01", "end_date": "2025-03-31", "raw_data": 134446}}]
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| Dec. 5, 2023, 4:23 p.m. |
Created
43
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[{"model": "core.projectfund", "pk": 39752, "fields": {"project": 9542, "organisation": 2, "amount": 504102, "start_date": "2022-11-01", "end_date": "2025-03-30", "raw_data": 102374}}]
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| Nov. 27, 2023, 2:13 p.m. |
Added
35
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{"external_links": []}
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| Nov. 21, 2023, 4:36 p.m. |
Created
43
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[{"model": "core.projectfund", "pk": 32448, "fields": {"project": 9542, "organisation": 2, "amount": 504102, "start_date": "2022-11-01", "end_date": "2025-03-30", "raw_data": 61620}}]
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| Nov. 21, 2023, 4:36 p.m. |
Created
41
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[{"model": "core.projectorganisation", "pk": 92703, "fields": {"project": 9542, "organisation": 11482, "role": "PP_ORG"}}]
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| Nov. 21, 2023, 4:36 p.m. |
Created
41
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[{"model": "core.projectorganisation", "pk": 92702, "fields": {"project": 9542, "organisation": 14105, "role": "LEAD_ORG"}}]
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| Nov. 21, 2023, 4:36 p.m. |
Created
40
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[{"model": "core.projectperson", "pk": 58164, "fields": {"project": 9542, "person": 15490, "role": "COI_PER"}}]
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| Nov. 21, 2023, 4:36 p.m. |
Created
40
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[{"model": "core.projectperson", "pk": 58163, "fields": {"project": 9542, "person": 16122, "role": "COI_PER"}}]
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| Nov. 21, 2023, 4:36 p.m. |
Created
40
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[{"model": "core.projectperson", "pk": 58162, "fields": {"project": 9542, "person": 13559, "role": "PI_PER"}}]
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| Nov. 20, 2023, 2:03 p.m. |
Updated
35
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{"title": ["", "Radiation Hardened robotics for remote INspectiOn - RHINO"], "description": ["", "\nIn 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.\n\nRetrieval 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.\n\nThis 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.\n\n"], "extra_text": ["", "\n\n\n\n"], "status": ["", "Active"]}
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| Nov. 20, 2023, 2:03 p.m. |
Added
35
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{"external_links": [38943]}
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| Nov. 20, 2023, 2:03 p.m. |
Created
35
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[{"model": "core.project", "pk": 9542, "fields": {"owner": null, "is_locked": false, "coped_id": "aa718c4c-ffc6-4ffe-bd40-8bc4419e4df3", "title": "", "description": "", "extra_text": "", "status": "", "start": null, "end": null, "raw_data": 61603, "created": "2023-11-20T13:28:01.989Z", "modified": "2023-11-20T13:28:01.989Z", "external_links": []}}]
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