Name : Felipe Lacerda Giro

Supervisors : Prof. Philippe Rigo (ULiège)

Co-supervisor : Prof. Jean-François Demonceau (ULiège), Christof Devriendt (VUB)

Funding : Energy Transition Fund (ETF)

Duration : 4 years

Structural Reliability Modeling and Updating for Offshore Wind Turbine Support Structures




he pursuit for efficiency pushes wind turbines further offshore, increasing water depth and deterioration exposure. Thus, the costs share related to support structure, mainly due to structural weight, increases, demanding more efficient structural designs. Inspection, monitoring and maintenance updates and controls risk of failure, and it can assist decision makers to reduce costs without disregarding structural reliability. However, such actions on different structural components have different consequences. With that in mind, this research proposes a reliability model that considers the component particularities of the support structure.

The main objective is to provide a method to model the structural reliability of the entire support structure. Difference in deterioration rate, accessibility, geometrical characteristics, among others, makes every component, and their contribution to the global reliability, unique. Component contribution knowledge can assist decision makers to efficiently employ their resources in actions that brings the highest benefit. To reach this propose, reliability model should consider actions (i.e., inspection, monitoring and maintenance) individually for each component.

The concurrent objective is to guarantee that the reliability assessment can be performed in a reasonable time. High number of components and actions can lead to complex (and thus computationally expensive) models. From the proposed reliability model, the most laborious computational process is the inference task. Inference, for this project propose, is the process to update the component deterioration state from new information provided by inspection and/or monitoring campaigns. So, one infers the component deterioration state every time a new information is gathered. A system with large number of components can make the reliability calculation unfeasible. Hence, this research also investigates innovative inference methods for structural reliability, focusing on methods that utilizes continuous state space, as Kalman Filters.

In summary, the proposed study aims to increase the model fidelity in order to assist the decision maker in the task of where, when and how to execute inspection, monitoring and maintenance actions. One can use this model for life extension assessment of existing wind turbine or, if design parameters are included to the model, to support engineers incorporate these actions to the design phase of the support structure.



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