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[{"model": "core.projectfund", "pk": 31188, "fields": {"project": 8414, "organisation": 508, "amount": 204031, "start_date": "2023-08-31", "end_date": "2025-08-30", "raw_data": 39844}}]
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[{"model": "core.projectorganisation", "pk": 88686, "fields": {"project": 8414, "organisation": 10130, "role": "PP_ORG"}}]
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[{"model": "core.projectorganisation", "pk": 88685, "fields": {"project": 8414, "organisation": 270, "role": "FELLOW_ORG"}}]
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[{"model": "core.projectorganisation", "pk": 88684, "fields": {"project": 8414, "organisation": 66, "role": "LEAD_ORG"}}]
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[{"model": "core.projectperson", "pk": 55548, "fields": {"project": 8414, "person": 11856, "role": "FELLOW_PER"}}]
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[{"model": "core.projectperson", "pk": 55547, "fields": {"project": 8414, "person": 11855, "role": "PI_PER"}}]
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[{"model": "core.projectperson", "pk": 55546, "fields": {"project": 8414, "person": 11856, "role": "PI_PER"}}]
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{"title": ["", "Digital Twins-based integrated corrosion fatigue prognosis of wind turbines Towers in modular energy islands"], "description": ["", "\nFacing the goal of climate neural set by the EU Green Deal, the modular energy island is suggested to utilise the attractive wind\npower at the deep sea. As a matter of factor, a prominent structural challenge arises, i.e., the corrosion fatigue deterioration of wind\ntowers under the combination of the harsh marine environment, prominent cyclic loads, and a copious number of welded\nconnections. Thus, the TwinsTower action aims to develop new and practical contributions towards a better understanding of the\ncorrosion fatigue of wind towers in modular energy islands, with both the physical model, inspection result and monitoring data\nintegrated. The experienced research (ER) will: (i) establish an integrated corrosion fatigue prediction model for wind towers in the\nmodular energy island; (ii) construct a digital twins-based prognosis approach for wind towers in modular energy islands, with the\nmonitoring and inspection result integrated.\nImplemented at the University of Birmingham, as supervised by the Chair Prof Charalampos Baniotopoulos, this action will enable the\nER to diversify his competence by developing his skills in wind energy research, data science, knowledge dissemination and\nexploitation, networking, supervision, teaching, research management and leadership. This action will also strongly benefit the ER's\ninter-sectoral and interdisciplinary expertise and strengthen the international network considering a secondment at the Ruhr-\nUniversität Bochum.\nA two-way transfer of knowledge is guaranteed since the action integrates the ER's experience in corrosion fatigue prediction,\nprobabilistic modelling of deterioration, and engineering practises as well as the hosts' expertise in tower design and detailing, deep\nlearning, and SHM data exploitation. To sum, the TwinsTower action could contribute to the EU's knowledge-based society,\npolicymakers and professionals by offering invaluable knowledge and a practical approach supporting the goal of climate neural.\n\n"], "extra_text": ["", "\n\n\n\n"], "status": ["", "Active"]}
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Jan. 28, 2023, 10:52 a.m. |
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{"external_links": [34429]}
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Jan. 28, 2023, 10:52 a.m. |
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[{"model": "core.project", "pk": 8414, "fields": {"owner": null, "is_locked": false, "coped_id": "48f2f2ed-8cf3-4075-9d05-3d876e47e5a0", "title": "", "description": "", "extra_text": "", "status": "", "start": null, "end": null, "raw_data": 39827, "created": "2023-01-28T10:48:45.122Z", "modified": "2023-01-28T10:48:45.122Z", "external_links": []}}]
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