| Feb. 13, 2024, 4:20 p.m. |
Created
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[{"model": "core.projectfund", "pk": 62850, "fields": {"project": 11047, "organisation": 2, "amount": 0, "start_date": "2021-10-01", "end_date": "2025-09-30", "raw_data": 178322}}]
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| Jan. 30, 2024, 4:24 p.m. |
Created
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[{"model": "core.projectfund", "pk": 55691, "fields": {"project": 11047, "organisation": 2, "amount": 0, "start_date": "2021-10-01", "end_date": "2025-09-30", "raw_data": 154551}}]
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| Jan. 2, 2024, 4:15 p.m. |
Created
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[{"model": "core.projectfund", "pk": 48495, "fields": {"project": 11047, "organisation": 2, "amount": 0, "start_date": "2021-10-01", "end_date": "2025-09-30", "raw_data": 133333}}]
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| Dec. 5, 2023, 4:23 p.m. |
Created
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[{"model": "core.projectfund", "pk": 41248, "fields": {"project": 11047, "organisation": 2, "amount": 0, "start_date": "2021-09-30", "end_date": "2025-09-29", "raw_data": 100442}}]
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| Nov. 27, 2023, 2:14 p.m. |
Added
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{"external_links": []}
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| Nov. 21, 2023, 4:38 p.m. |
Created
43
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[{"model": "core.projectfund", "pk": 33953, "fields": {"project": 11047, "organisation": 2, "amount": 0, "start_date": "2021-09-30", "end_date": "2025-09-29", "raw_data": 58725}}]
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| Nov. 21, 2023, 4:38 p.m. |
Created
41
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[{"model": "core.projectorganisation", "pk": 98551, "fields": {"project": 11047, "organisation": 12144, "role": "STUDENT_PP_ORG"}}]
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| Nov. 21, 2023, 4:38 p.m. |
Created
41
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[{"model": "core.projectorganisation", "pk": 98550, "fields": {"project": 11047, "organisation": 14392, "role": "LEAD_ORG"}}]
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| Nov. 21, 2023, 4:38 p.m. |
Created
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[{"model": "core.projectperson", "pk": 62023, "fields": {"project": 11047, "person": 15395, "role": "SUPER_PER"}}]
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| Nov. 21, 2023, 4:38 p.m. |
Created
40
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[{"model": "core.projectperson", "pk": 62022, "fields": {"project": 11047, "person": 16115, "role": "SUPER_PER"}}]
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| Nov. 20, 2023, 2:04 p.m. |
Updated
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{"title": ["", "A Bayesian Neural Network (BNN) Machine Learning (ML) Surrogate Modelling Framework for High-Fidelity Thermal Fatigue Modelling of Components"], "description": ["", "\nNational energy grid and power distribution infrastructure, within developed and developing countries, are currently undergoing significant modification to produce so-called smart grid infrastructure. In these smart grids there will be a mixture of dynamically evolving or intermittent renewable energy supply augmented by a proportion of base-load electrical power. There is a widespread misconception that nuclear power plants (NPPs) can only provide relatively inflexible base-load power to any national energy grid networks. However, this is significantly affecting the long-term prospects of the nuclear sector's role in delivering cost effective electrical power within the more heterogeneous and mixed power generation environment that is evolving around the world. Increasing electrical power generation is being dominated by intermittent renewable energy forms. Nuclear power generation will need to adapt to this new smart grid infrastructure.\n\n"], "extra_text": ["", "\n\nPotential Impact:\nIt cannot be overstated how important reducing CO2 emissions are in both electricity production for homes and industry but also in reducing road pollution by replacing petrol/diesel cars with electric cars in the next 20 years. These ambitions will require a large growth in electricity production from low carbon sources that are both reliable and secure and must include nuclear power in this energy mix. Such a future will empower the vision of a prosperous, secure nation with clean energy. To do this the UK needs more than 100 PhD level people per year to enter the nuclear industry. This CDT will impact this vision by producing 70, or more, both highly and broadly trained scientists and engineers, in nuclear power technologies, capable of leading the UK new build and decommissioning programmes for future decades. These students will have experience of international nuclear facilities e.g. ANSTO, ICN Pitesti, Oak Ridge, Mol, as well as a UK wide perspective that covers aspects of nuclear from its history, economics, policy, safety and regulation together with the technical understanding of reactor physics, thermal hydraulics, materials, fuel cycle, waste and decommissioning and new reactor designs. These individuals will have the skill set to lead the industry forward and make the UK competitive in a global new build market worth an estimated £1.2tn. Equally important is reducing the costs of future UK projects e.g. Wylfa, Sizewell C by 30%, to allow the industry and new build programme to grow, which will be worth £75bn domestically and employ tens of thousands per project. \n\nWe will deliver a series of bespoke training courses, including on-line e-learning courses, in Nuclear Fuel Cycle, Waste and Decommissioning; Policy and Regulation; Nuclear Safety Management; Materials for Reactor Systems, Innovation in Nuclear Technology; Reactor Operation and Design and Responsible Research. These courses can be used more widely than just the CDT educating students in other CDTs with a need for nuclear skills, other university courses related to nuclear energy and possibly for industry as continual professional development courses and will impact the proposed Level 8 Apprenticeship schemes the nuclear industry are pursuing to fill the high level skills gap. \n\nThe CDT will deliver world-class research in a broad field of nuclear disciplines and disseminate this work through outreach to the public and media, international conferences, published journal articles and conference proceedings. It will produce patents where appropriate and deliver impact through start-up companies, aided by Imperial Innovations, who have a track record of turning research ideas into real solutions. By working and listening to industry, and through the close relationships supervisory staff have with industrial counterparts, we can deliver projects that directly impact on the business of the sponsors and their research strategies. There is already a track record of this in the current CDT in both fission and fusion fields. For example there is a student (Richard Pearson) helping Tokamak Energy engage with new technologies as part of his PhD in the ICO CDT and as a result Tokamak Energy are offering the new CDT up to 5 studentships. \n\nAnother impact we expect is an increasing number of female students in the CDT who will impact the industry as future leaders to help the nuclear sector reach its target of 40% by 2030. \nThe last major impact of the CDT will be in its broadening scope from the previous CDT. The nuclear industry needs to embrace innovation in areas such as big data analytics and robotics to help it meet its cost reduction targets and the CDT will help the industry engage with these areas e.g. through the Bristol robotics hub or Big Data Institute at Imperial.\n\nAll this will be delivered at a remarkable value to both government and the industry with direct funding from industry matching the levels of investment from EPSRC.\n\n\n"], "status": ["", "Active"]}
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| Nov. 20, 2023, 2:04 p.m. |
Added
35
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{"external_links": [45547]}
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| Nov. 20, 2023, 2:04 p.m. |
Created
35
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[{"model": "core.project", "pk": 11047, "fields": {"owner": null, "is_locked": false, "coped_id": "b96bdf95-d62a-4624-89fe-ec2bf4d1b3b2", "title": "", "description": "", "extra_text": "", "status": "", "start": null, "end": null, "raw_data": 58708, "created": "2023-11-20T13:41:18.759Z", "modified": "2023-11-20T13:41:18.759Z", "external_links": []}}]
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