Reliability-Based Design of Wind Turbine Foundations: Geotechnical Site Assessment

With industrialization taking off in the 18th century, a dramatic increase of carbon dioxide emission began due to burning of fossil fuels. The heat-trapping nature of carbon dioxide causes global warming resulting in major concern about climate change as well as in an increased demand for more reliable, affordable, clean and renewable energy. Wind turbines have gained popularity among other renewable energy generators by having both technically and economically efficient features and by offering competitive production prices compared to other renewable energy sources. Therefore, it is a key green energy technology in breaking the fossil fuel dependency. The costs of foundations for offshore wind turbines typically amount to 20–30% of the total wind turbine budget. Thus, an optimized design of these foundations will improve the cost effectiveness by matching a suitable target reliability level.

The overall aim of the present PhD thesis is to facilitate a low-cost foundation design for future offshore wind farms by focusing on the geotechnical site assessment. First, a number of well-established techniques for soil classification based on cone penetration test (CPT) data have been investigated for a local case in order to estimate the inherent uncertainties in these models. For the purpose of verification and prediction of the best method for the region, a comparison was made with laboratory test results on samples retrieved from boreholes at the site.

In addition to this, several seismic CPTs were performed in sand and clay in order to estimate the small-strain shear modulus of the soil as a key parameter in analysis and design of foundations, and the soil type of the region was estimated based on this value. Furthermore, the shear moduli obtained from the seismic tests were compared with moduli estimated from cone data using different empirical relations. The later part of the thesis concerns the assessment of the spatial correlation lengths of CPTu data in a sand layer. Results from two different sites in northern Denmark indicated quite strong anisotropy with significantly shorter spatial correlation lengths in the vertical direction as a result of the depositional process. The normalized cone resistance is a better estimator of spatial trends compared to the normalized friction ratio.

In geotechnical engineering analysis and design, practitioners ideally would like to know the soil properties at many locations, but achieving this goal can be unrealistic and expensive. Therefore, developing ways to determine these parameters using statistical approaches is of great interest. This research employs a random field model to deal with uncertainty in soil properties due to spatial variability by analysing CPTu data from a sandy site in northern Denmark. Applying a Kriging interpolation approach gave a best estimate of properties between observation points in the random field, and the influence of spatial correlation length on the results was investigated. Results show that a longer correlation length reduces the estimator error and results in more variation in the estimated values between the interpolated points.