Insights into corrosion-fatigue deterioration in offshore wind turbine structures through digital twin applications
Abstract
Offshore wind turbines (OWTs) are critical for the global energy transition, but their long-term structural integrity is threatened by synergistic corrosion-fatigue (C-F) in the harsh marine environment, necessitating prognostic frameworks that extend beyond traditional inspection regimes. This paper addresses this challenge by presenting a comprehensive, cross-domain synthesis of the state of the art in applying digital twin (DT) technology to this problem. Recognising the emerging and multidisciplinary nature of the field, a hybrid review methodology was employed, combining a systematic, Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-guided literature search with an expert-driven inclusion of foundational, cross-domain, and codified literature to construct a holistic map of current capabilities. The review synthesises knowledge across three core areas: (1) the fundamental mechanisms of C-F in marine environments; (2) the architectural models of DTs, from physics-based to hybrid, artificial intelligence (AI)-driven models; and (3) the suite of enabling technologies, including structural health monitoring (SHM), robotics, and the Internet of Things (IoT). Key findings include a detailed vulnerability analysis of critical OWT structural components, a critical comparison of DT modelling architectures based on their capability and readiness, and a framework for ranking the evidentiary strength of validation approaches (from simulation to field deployment). By distinguishing between established, code-consistent practices and emerging research, this work provides a clear roadmap for researchers and practitioners, aiming to accelerate the development and validation of robust DT solutions for enhancing the safety and reliability of OWTs.