Large-scale cultivation of seaweed presents opportunities for multiple global challenges currently at play. Cultivated seaweed can provide a sustainable source of protein for humans and cattle without competing for land, freshwater supply or the use of fertilisers. Kelp forests are known to be a solid basis for an elaborate biome that supports biodiversity in areas that have been damaged by over-fishing or rising sea temperatures. Additionally, kelp forests can lock-in large amounts of Blue Carbon, expanding the oceans’ buffering capacity to mitigate anthropogenic emissions. Furthermore, with their densely seeded lines, offshore kelp farms are found to attenuate wave amplitude, thus providing coastal protection and benefits like increased workability for offshore operations. Both academic publications and industry reviews underline the potential of this sector and significant growth in cultivation is expected in the near future.

Methods currently used for quantification of the damping effects of large-scale offshore kelp farms are diverse and entail varying degrees of accuracy and computational cost. Experimental observations that support the outcomes of these methods are limited to scaled experiments in wave flumes, with various methods used to mimic vegetation. No convergence is found in the most suitable methods for application to large-scale offshore kelp farms.
This research presents a novel modelling framework based upon the Finite Element method, implemented using Julia Programming Language. The effects of the vegetation on the wave climate are represented with a Darcy-Forchheimer term borrowed from porous medium flow theory, including a linear and a quadratic resistance term. The framework comprises a numerical wave tank, using the incompressible Navier Stokes equations. The single-phase model captures the free surface using the coupling of dynamic pressure with a virtual elevation variable through a linearized transpiration boundary condition. Wave energy dissipation is shown to increase significantly by moving the farm structure close to the water surface. Similarly, a decrease in relative water depth - compared to the vegetated height - increases damping potential. Wave period is found to be of strong influence on dissipation, where short waves are attenuated more. Scaling vegetation length with wave length, however, diminishes the reduction in damping of longer waves. Conversely, wave amplitude is shown to be of less influence on the transmission of amplitude through a vegetated patch.
The framework presents a method that is easily scalable, flexible in application on a wide range of flows and vegetation characteristics, and at reasonable computational cost. Introduction of both the linear and quadratic terms extends applicability compared to traditional methods. The approach is verified using convergence studies, application of the model is validated by comparison to existing experimental data. It is shown that experimental set-ups can be reproduced effectively, and simulation results coincide with experimental findings. Validation of outcomes on scales larger than common wave tanks was found unfeasible due to a lack of measurement data. A theoretical case study was performed to predict wave damping of a full-scale kelp farm, demonstrating promising potential with up to 40% wave energy reduction at the local peak wave period.

Further research into the establishment of the Darcy- and Forchheimer-coefficients is recommended. A preliminary range of values has been found, based upon calibration on existing experiments that represent realistic ranges of vegetation characteristics. Furthermore, the main conditions of the flow and vegetation that dictate damping potential are identified. On this basis, research into a physics-based determination of the coefficients is recommended. Additionally, full-scale measurements are advised to validate application on future kelp farm designs.
Through this novel approach, the range of application is increased compared to existing methods, while straightforward setup and usage are governed, and limited computational costs allow for simulation without the need for a dedicated computer setup. The framework is shown to be robust by generating consistent simulation results. In summary, the established framework shows to be a good alternative to existing approaches to investigate the wave damping potential of large-scale offshore kelp farms.

In contrast to traditional power cables for bottom-founded offshore wind turbines, power cables for floating wind turbines penetrate the water column and are exposed to cyclic loading. Due to the dynamic nature of the cable loading, the cables are prone to fatigue failure. Since the evaluation of the fatigue life of complex structures, like power cables, has to deal with a certain degree of uncertainty, fatigue safety factors are introduced. These factors ensure a desired probability of failure based on the degree of uncertainty present in the modeling of the fatigue life. Limited experience in the evaluation of the fatigue life of dynamic power cables is found in the literature, and no sources have been found attempting to calibrate the prescribed fatigue safety factor. Currently, a fatigue safety factor of 10 is advised. This implies that there is much room for reduction in the uncertainties, meaning that there is a potential for making the cables cheaper and more reliable, which will in turn make floating wind energy more competitive with other (renewable) energy sources.
Due to the lack of available literature, comparisons with umbilicals and flexible risers are made. Different methods for the evaluation of fatigue safety factors for flexible risers are evaluated, and judged on how applicable they are to use on dynamic power cables. It is found that a reliability based approach is most suitable for this purpose.
A case study is carried out for a presently relevant scenario to put the proposed method into practice. It is concluded that for a safety class corresponding to a required maximum probability of failure of 10^-3 in the last operational year, a fatigue safety factor of 3.5 is needed. This safety factor is required for the wave-load induced fatigue, as opposed to the seabed induced fatigue, to which the dynamic power cable is less vulnerable nearby the touch-down zone. 
The main parameter driving the uncertainty in the fatigue analysis is the sensitivity of the local stress analysis, which is in line with what has been found for similar studies for the oil & gas industry. In order to bring down the cost of dynamic power cables, and make them more reliable, more accurate local stress analysis models need to be developed, being validated against test data, in order to reduce the standard deviation of the local stress computation.