Experiments
In this project, two new series of wave tank tests have been conducted at the Kelvin Hydrodynamics Laboratory at the University of Strathclyde in Glasgow, UK, and at the State Key Laboratory of Coastal and Offshore Engineering at Dalian University of Technology in Dalian, China.
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Additionally, some previously gathered experimental data has been reanalysed to complement these studies.
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For more detailed information, please click here.
Numerical simulations
In this project, we use Computational Fluid Dynamics (CFD) to broaden our machine learning model's database with additional scaling tests. Two CFD models have been employed for this purpose: the open-source software OpenFOAM and our in-house Particle-In-Cell (PIC) model. Both models have undergone rigorous validation and have proven accurate in replicating high-order non-linear force harmonics.
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For more detailed information, please click here.
Stokes-GP model
To develop a fast and accurate model for predicting nonlinear wave loading on vertical cylinders, typically used in monopile offshore wind turbine foundations, we have adopted a ‘Stokes-type’ force model (Chen et al., 2018). This model approximates the amplitude of higher harmonics of force by correlating these to the linear force time series raised to appropriate powers, modulated by amplitude and phase coefficients. We have reanalysed previous experimental data and conducted new experiments to expand the parameter space and establish a force coefficients database for engineering applications. A machine learning model, known as the Gaussian Process (GP) model, is utilised to interpolate this database and predict higher-order force coefficients, as detailed in (Tang et al., 2024).
The Stokes-GP model will be published later this year as an open-access engineering tool.
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