工程可靠性与随机力学国际联合研究中心

2025年第16期（总第108期）学术报告

工程力学研究中心第62期学术报告

土木工程学院院级高等讲堂

报告主题

TOPIC

从结构控制到数字孪生：海上风机的动力学与机器学习

From Structural Control to Digital Twins: Dynamics and Learning in Offshore Wind Turbines

报告人

SPEAKER

Prof. Breiffni Fitzgerald

Associate Professor, School of Engineering, Trinity College Dublin, Ireland

报告时间

TIME

2025年10月27日（周一）上午10:00-11:00

报告地点

VENUE

同济大学土木大楼 A804

主持人

CHAIR

张自立教授、陈建兵教授

联系人：牛立志

报告摘要

Abstract

The next generation of offshore wind turbines presents unprecedented challenges in structural dynamics, control, and reliability. As turbines grow taller and more flexible, dynamic coupling between aerodynamic, hydrodynamic, and structural loads becomes increasingly pronounced, demanding advanced strategies for vibration mitigation and real-time monitoring. This lecture explores the evolution of offshore wind turbine dynamics research from model-based control to data-driven intelligence. It begins with recent advances in vibration control using inerter-based tuned mass dampers, highlighting their potential to enhance robustness under stochastic wind and wave excitations. The talk then transitions to data-driven modelling and machine learning approaches for dynamic response prediction, virtual sensing, and fatigue estimation. By integrating physics-informed neural networks with high-fidelity aeroelastic simulations, this work aims to bridge the gap between analytical control design and digital-twin-based structural health monitoring. The lecture concludes with perspectives on reliability, uncertainty quantification, and future directions for intelligent, resilient offshore energy systems.

报告人简介

Speaker Bio

Dr. Breiffni Fitzgerald is internationally recognised for his research at the interface of structural dynamics, vibration control, and wind energy. An Associate Professor in the School of Engineering at Trinity College Dublin, his work focuses on enhancing the dynamic performance, reliability, and resilience of tall buildings and offshore wind turbines through advanced control concepts such as inerter-based damping and data-driven modelling. By integrating classical structural dynamics with modern machine learning approaches, his research provides new insights into mitigating wind-induced vibrations across a range of flexible and wind-sensitive structures. He has published widely in leading journals and serves as an editor of Wind Energy, the flagship international journal in the field. An active member of the European Academy of Wind Energy, he contributes to advancing the discipline at an international level.

His contributions have been recognised through election to the Fellowship of Trinity College Dublin in 2025, the Institution of Structural Engineers (IStructE) Research into Practice Award in 2024, the Trinity College Dublin Teaching Excellence Award in 2023, and the Structural Engineering Award from the Council on Tall Buildings and Urban Habitat in 2022. A Chartered Engineer with Engineers Ireland and ASCE, he collaborates extensively with industry to address practical challenges in the design, monitoring, and vibration control of offshore wind energy systems and other wind-sensitive infrastructure.