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Reference Number EP/X022765/1
Title Digital Twins-based integrated corrosion fatigue prognosis of wind turbines Towers in modular energy islands
Status Started
Energy Categories Renewable Energy Sources (Wind Energy) 100%;
Research Types Basic and strategic applied research 100%
Science and Technology Fields PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 20%;
ENGINEERING AND TECHNOLOGY (Mechanical, Aeronautical and Manufacturing Engineering) 80%;
UKERC Cross Cutting Characterisation Not Cross-cutting 100%
Principal Investigator Professor C Baniotopoulos

Civil Engineering
University of Birmingham
Award Type Standard
Funding Source EPSRC
Start Date 01 March 2023
End Date 28 February 2025
Duration 24 months
Total Grant Value £204,031
Industrial Sectors
Region West Midlands
Programme UKRI MSCA
Investigators Principal Investigator Professor C Baniotopoulos , Civil Engineering, University of Birmingham (100.000%)
  Industrial Collaborator Project Contact , Ruhr-University Bochum (RUB), Germany (0.000%)
Web Site
Abstract Facing the goal of climate neural set by the EU Green Deal, the modular energy island is suggested to utilise the attractive windpower at the deep sea. As a matter of factor, a prominent structural challenge arises, i.e., the corrosion fatigue deterioration of windtowers under the combination of the harsh marine environment, prominent cyclic loads, and a copious number of weldedconnections. Thus, the TwinsTower action aims to develop new and practical contributions towards a better understanding of thecorrosion fatigue of wind towers in modular energy islands, with both the physical model, inspection result and monitoring dataintegrated. The experienced research (ER) will: (i) establish an integrated corrosion fatigue prediction model for wind towers in themodular energy island; (ii) construct a digital twins-based prognosis approach for wind towers in modular energy islands, with themonitoring and inspection result integrated.Implemented at the University of Birmingham, as supervised by the Chair Prof Charalampos Baniotopoulos, this action will enable theER to diversify his competence by developing his skills in wind energy research, data science, knowledge dissemination andexploitation, networking, supervision, teaching, research management and leadership. This action will also strongly benefit the ER'sinter-sectoral and interdisciplinary expertise and strengthen the international network considering a secondment at the Ruhr-Universität Bochum.A two-way transfer of knowledge is guaranteed since the action integrates the ER's experience in corrosion fatigue prediction,probabilistic modelling of deterioration, and engineering practises as well as the hosts' expertise in tower design and detailing, deeplearning, and SHM data exploitation. To sum, the TwinsTower action could contribute to the EU's knowledge-based society, policymakers and professionals by offering invaluable knowledge and a practical approach supporting the goal of climate neural
Publications (none)
Final Report (none)
Added to Database 08/03/23