Influence of advanced load simulation models on fatigue design of jackets for offshore wind turbines.

Constant developments in the field of offshore wind energy have increased the range of water depths at which wind farms are planned to be installed. Therefore, in addition to monopile support structures suitable in shallow waters (up to 30 m), different types of support structures, able to withstand severe sea conditions at the greater water depths, have been developed. For water depths above 30 m, the jacket is one of the preferred support types. Jacket represents a lightweight support structure, which, in combination with complex nature of environmental loads, is prone to highly dynamic behavior. As a consequence, high stresses with great variability in time can be observed in all structural members. The highest concentration of stresses occurs in joints due to their nature (structural discontinuities) and due to the existence of notches along the welds present in the joints. This makes them the weakest elements of the jacket in terms of fatigue. In the numerical modeling of jackets for offshore wind turbines, a reduction of local stresses at the chord-brace joints, and consequently an optimization of the model, can be achieved by implementing joint flexibility in the chord-brace joints. Therefore, in this work, the influence of joint flexibility on the fatigue damage in chord-brace joints of a numerical jacket model, subjected to advanced load simulations, is studied.

Observations and modeling of the Marginal Ice Zone

Global climate change in recent decades has strongly influenced the Arctic generating pronounced warming accompanied by significant reduction of sea ice in seasonally ice-covered seas and a dramatic increase of open water regions exposed to wind [Stephenson et al., 2011]. By strongly scattering the wave energy, thick multiyear ice prevents swell from penetrating deeply into the Arctic pack ice. However, with the recent changes affecting Arctic sea ice, waves gain more energy from the extended fetch and can therefore penetrate further into the pack ice. Arctic sea ice also appears weaker during melt season, extending the transition zone between thick multi-year ice and the open ocean. This region is called the Marginal Ice Zone (MIZ). In the Arctic, the MIZ is mainly encountered in the marginal seas, such as the Nordic Seas, the Barents Sea, the Beaufort Sea and the Labrador Sea. Formed by numerous blocks of sea ice of various diameters (floes) the MIZ, under certain conditions, allows maritime transportation stimulating dreams of industrial and touristic exploitation of these regions and possibly allowing, in the next future, a maritime connection between the Atlantic and the Pacific. With the increasing human presence in the Arctic, waves pose security and safety issues. As marginal seas are targeted for oil and gas exploitation, understanding and predicting ocean waves and their effects on sea ice become crucial for structure design and for real time safety of operations. The juxtaposition of waves and sea ice represents a risk for personnel and equipment deployed on ice, and may complicate critical operations such as platform evacuations. The risk is difficult to evaluate because there are no long-term observations of waves in ice, swell events are difficult to predict from local conditions, ice breakup can occur on very short time-scales and wave-ice interactions are beyond the scope of current forecasting models [Liu and Mollo-Christensen, 1988,Marko, 2003]. In this thesis, a newly developed Waves in Ice Model (WIM) [Williams et al., 2013a,Williams et al., 2013b] and its related Ocean and Sea Ice model (OSIM) will be used to study the MIZ and the improvements of wave modeling in ice infested waters. The following work has been conducted in collaboration with the Nansen Environmental and Remote Sensing Center and within the SWARP project which aims to extend operational services supporting human activity in the Arctic by including forecast of waves in ice-covered seas, forecast of sea-ice in the presence of waves and remote sensing of both waves and sea ice conditions. The WIM will be included in the downstream forecasting services provided by Copernicus marine environment monitoring service.