Requirements for the application of the Digital Twin Paradigm to offshore wind turbine structures for uncertain fatigue analysis

The Digital Twin (DT) paradigm offers an extension of simulation model utility into the operational phase of an engineering asset. The goal is a simulation ‘‘twinned’’ with observed data that reflects the actual performance of the asset. However, exploring sources of uncertainty for both the physical asset and the simulation model are a challenge. For example, random metocean conditions, and uncertainty on model parameters and response behaviour of offshore wind turbine (OWT) structures, contribute to uncertainty for predicted life under fatigue. In-service assessment of OWT structures will benefit from twinning simulations and observed data, where a framework to treat this uncertainty is defined. The DT needs to capture state, condition, and behaviour to a level that allows quantification and propagation of uncertainty for reliability analysis. Using a DT, built for fatigue assessment of bolted ring-flanges on OWT support structures, this paper explores the challenges and opportunities in defining uncertainties of interest. We propagate these uncertainties through the DT in a coherent manner using a Gaussian Process (GP) surrogate modelling approach, efficiently emulating a computationally expensive numerical simulator. The GP is an attractive surrogate model method given this computational efficiency, in addition to providing an estimate of prediction uncertainty at unobserved points
in the output space. The use of the GP surrogate model is included within a definition of the Surrogate DT, a framework including ‘‘fast’’ and ‘‘slow’’  twinning processes. We define six requirements to apply DTs to OWT structures which provide practical guidelines for modelling this complex asset under  uncertainty.