Abstract
This paper presents a probabilistic framework for updating the structural reliability of offshore wind turbine substructures based on digital twin information. In particular, the information obtained from digital twins is used to quantify and update the uncertainties associated with the structural dynamics and load modeling parameters in fatigue damage accumulation. The updated uncertainties are included in a probabilistic model for fatigue damage accumulation used to update the structural reliability. The updated reliability can be used as input to optimize decision models for operation and maintenance of existing structures and design of new structures. The framework is exemplified based on two numerical case studies with a representative offshore wind turbine and information acquired from previously established digital twins. In this context, the effect of updating soil stiffness and wave loading, which constitute two highly uncertain and sensitive parameters, is investigated. It is found that updating the soil stiffness significantly affects the reliability of the joints close to the mudline, while updating the wave loading significantly affects the reliability of the joints localized in the splash zone. The increased uncertainty related to virtual sensing, which is employed to update wave loading, reduces structural reliability.
Highlights
The offshore wind industry has experienced significant growth over the last decade [1].As a result, the number of offshore wind turbines operating in Europe has reached 5402 in 2020 [2], with much more planned to be installed worldwide in the close future [3].The typical lifetime of an offshore wind turbine ranges between 20 and 25 years, which means that over the coming years a large number of these structures reach their intended lifetime, and operators will have to take actions regarding their assets
We propose a probabilistic framework for updating structural reliability of offshore wind substructures based on new information from digital twins
The digital twin information is consistently included in the framework by updating the uncertainty related to structural dynamics and load modeling and propagating this uncertainty to the fatigue damage accumulation
Summary
The offshore wind industry has experienced significant growth over the last decade [1]. Extended a conceptual framework for updating decision models based on information from a digital twin, initially proposed by Tygesen et al [7], to be applied to offshore wind substructures. We outline the framework by Augustyn et al [19] beyond its conceptual level and propose a probabilistic method for updating the structural reliability of offshore wind turbine substructures based on new information obtained from digital twins. A more economically feasible alternative, in the form of condition-based monitoring, is typically investigated for offshore wind applications [27,28] In this context, condition monitoring data can be applied to identify structural damage, and the resulting integrity information can be employed for updating reliability [29].
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