Offshore wind farms are being built at an unprecedented pace in the North Sea. The Dutch government is aiming for a CO2 neutral energy supply by 2050 and vast cost reductions have turned (offshore) wind energy into a worthy competitor for other (green) energy sources. Most of the planned wind farms in the Dutch North Sea are located in areas where the seabed is covered with sand waves. In the North Sea these sand waves have lengths of 100-1000 m, heights of 1-8 m and they migrate with rates of up to 10 m/year (Morelissen et al., 2003). Sand wave migration and changes in shape, may cause a significant rise or drop in local bed level. This bed level variation over time could decrease the stability of foundations or bed protections or cause exposure of cables and pipelines.
Various offshore infrastructural projects, like offshore wind farms, thus require long term (30-50 years) predictions of the seabed dynamics. Currently data-driven methods are used to determine the range of expected bed levels. However, the uncertainty in these predictions is significant, with sand waves being the largest source of uncertainty. Furthermore, no real understanding of the systems at hand forms the base of these predictions. Not many attempts have been made to accurately model sand wave dynamics in real-life situations using a process based model. Since sand waves often have steep slopes in migration direction, a need for small numerical grid sizes arises. On the other hand oceanic hydrodynamics are affected by large scale bed forms. To include (the influence of) these bed forms, large model domains are required. This makes numerical modelling of sand wave fields rather difficult due to the balance between grid sizes and computation time. The newly developed Delft3D Flexible Mesh (FM) model may be able to overcome some of these problems.
Through the use of unstructured grids, the desired level of detail can be reached in certain sand wave areas. In combination with the possibility to run simulations in parallel, on multiple cores, computation times can be reduced significantly. However, the Delft3D FM model has not yet been used for the prediction of sand wave dynamics. The aim of this research is to find the opportunities and challenges of the Delft3D FM model for quantitative modelling of sand wave dynamics in the North Sea.
Through two case studies various opportunities and challenges for predicting sand wave dynamics using Delft3D FM are discovered. The Delft3D FM model showed a significant reduction of computation times for a 2DV case using a single core compared to Delft3D-4. For parallel simulations, using multiple cores, an approximately linear further reduction of computation time is observed in a 2DV setting. Furthermore, the possibility of unstructured grids presents a solution for the small grid sizes needed in sand wave areas. Other computational
gains are realized through a morphological scale factor (which is also
ncorporated in Delft3D-4), optimized time-step management and a new type of boundary conditions. This new boundary condition imposes both water level and flow velocity over depth in both horizontal directions. In this way the local flow conditions are accurately represented and the influence of bed forms outside the model domain can easily be incorporated. This potentially eliminates the need for buffer zones.
Challenges for the application of Delft3D FM on sand wave cases are found in amongst others the availability of data. When less data on local hydrodynamics is available the accurate representation of processes driving sand wave dynamics becomes more difficult. Furthermore the inclusion of sub-grid processes, like the growth and migration of megaripples, could be problematic. In the model case studies no calibration was carried out. This calibration could potentially increase the effort needed to apply Delft3D FM to real life sand wave cases.
Furthermore, the Delft3D FM model is still in development and significant differences between the results of different versions of Delft3D FM were observed. Care should be taken when applying a new version of Delft3D
FM. The model is however being developed in collaboration with users which ensures quick feedback and thus stimulates improvement of the results between versions.
Recommended research includes extended exploration of the 3D effects influencing sand wave dynamics. Furthermore, improvement of morphological results and optimization of the model set-up will increase the applicability
of Delft3D FM in an engineering setting. A model run forced by two Riemann boundaries showed improved morphological results, although the hydrodynamics were not well represented. These results might indicate
where differences with reality originate. Examples of such differences are overestimation of peak velocities, exclusion of wind-driven currents and exclusion of processes like suspended sediment transport, free surface waves
and grain size sorting. Further exploration of these factors could enhance the predictive capacities of Delft3D FM. Applying the model at other locations in the North Sea will help determine the overall applicability of the model.
Through this extended research the full potential of the Delft3D FM model can be discovered and prepared for future engineering applications. Insights gained into the processes influencing sand waves dynamics, through the use of Delft3D FM, could pave the way for more nature based solutions, thus reducing the need for dredging. In this way Delft3D FM could contribute to reducing risks, costs and environmental impact of offshore construction projects in sand wave areas.