Digital Twins-based integrated corrosion fatigue prognosis of wind turbines Towers in modular energy islands

面对欧盟绿色协议设定的气候神经目标，模块化能源岛被建议利用深海诱人的风能。作为一个因素，出现了一个突出的结构挑战，即在恶劣的海洋环境、突出的循环荷载和大量焊接连接的共同作用下，风塔的腐蚀疲劳劣化。因此，TwinsTower行动旨在通过物理模型、检测结果和监测数据的集成，为更好地了解模块化能源岛上风塔的腐蚀疲劳做出新的和实际的贡献。经验研究(ER)将：(I)为模块化能源岛的风塔建立一个综合的腐蚀疲劳预测模型；(Ii)为模块化能源岛的风塔建立一个基于数字双胞胎的预测方法，并将监测和检查结果整合在一起。这项行动将在伯明翰大学实施，由主席Charalampos Baniotopoulos教授监督，通过发展他在风能研究、数据科学、知识传播和开发、网络、监督、教学、研究管理和领导方面的技能，使他的能力多样化。这一行动还将极大地有利于ER的跨部门和跨学科专业知识，并加强考虑借调到波鸿鲁尔大学的国际网络。由于该行动整合了ER在腐蚀疲劳预测、恶化的概率建模和工程实践方面的经验，以及东道主在塔楼设计和细节、深造和SHM数据开发方面的专业知识，因此确保了双向知识转移。总而言之，TwinsTower行动可以通过提供宝贵的知识和支持气候神经目标的实际方法，为欧盟的知识型社会、政策制定者和专业人士做出贡献。

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.