Facing the goal of climate neural set by the EU Green Deal, the modular energy island is suggested to utilise the attractive wind
power at the deep sea. As a matter of factor, a prominent structural challenge arises, i.e., the corrosion fatigue deterioration of wind
towers under the combination of the harsh marine environment, prominent cyclic loads, and a copious number of welded
connections. Thus, the TwinsTower action aims to develop new and practical contributions towards a better understanding of the
corrosion fatigue of wind towers in modular energy islands, with both the physical model, inspection result and monitoring data
integrated. The experienced research (ER) will: (i) establish an integrated corrosion fatigue prediction model for wind towers in the
modular energy island; (ii) construct a digital twins-based prognosis approach for wind towers in modular energy islands, with the
monitoring and inspection result integrated.
Implemented at the University of Birmingham, as supervised by the Chair Prof Charalampos Baniotopoulos, this action will enable the
ER to diversify his competence by developing his skills in wind energy research, data science, knowledge dissemination and
exploitation, networking, supervision, teaching, research management and leadership. This action will also strongly benefit the ER's
inter-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, deep
learning, 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.