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

基于数字孪生的模块化能源岛风力涡轮机塔架腐蚀疲劳综合预测

• 批准号: EP/X022765/1
• 负责人: Charalampos Baniotopoulos
• 金额: $ 26万
• 依托单位: University of Birmingham
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FX022765%2F1
• 关键词: Digital; Twins; based; integrated; corrosion

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.

面对欧盟绿色交易的气候神经设定的目标，建议模块化能量岛利用深海中有吸引力的风力。就因素而言，出现了一个突出的结构挑战，即，在Harmsh海洋环境的组合，突出的循环载荷和大量的焊接连接组合下，腐蚀疲劳确定了风能。这是Twinstaper行动旨在为模块化岛上风塔的腐蚀疲劳提供新的和实践的贡献，并具有物理模型，检查结果和监视数据依据。经验丰富的研究（ER）将：（i）为模块化岛中的风塔建立一个综合的腐蚀疲劳预测模型； （ii）在伯明翰大学进行了核心和检查结果，在模块化岛上建立了一种基于数字双胞胎的预后方法，以进行模块化和检查结果，并在伯明翰大学进行了整合。 This action will also strongly benefit the ER'sinter-sectoral and interdisciplinary expertise and strengthen the international network considering a second 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 definition, and engineering practices as well as the hosts' expertise in tower design and detailing, deeperning, and SHM data剥削。总而言之，双重行动可以通过提供宝贵的知识和支持气候神经目标的实用方法来为欧盟的知识社会，决策者和专业人士做出贡献。

项目成果

Life-Cycle of Structures and Infrastructure Systems - PROCEEDINGS OF THE EIGHTH INTERNATIONAL SYMPOSIUM ON LIFE-CYCLE CIVIL ENGINEERING (IALCCE 2023), 2-6 JULY, 2023, POLITECNICO DI MILANO, MILAN, ITALY

结构和基础设施系统的生命周期 - 第八届生命周期土木工程国际研讨会 (IALCCE 2023) 论文集，2023 年 7 月 2-6 日，米兰理工大学，意大利米兰

• DOI: 10.1201/9781003323020-167
• 发表时间: 2023
• 作者: Amodio S