The geotechnical conditions of the soil can fluctuate greatly across the wind farm. This is an issue since geotechnical modelling is the base of the structural design of an offshore wind farm, and the efficient installation of the wind turbines depends on its accuracy. This paper deals with the characterization of the seabed, predicting the soil properties over the total affected area by a wind farm, with the challenge to reduce the required data samples in the site investigation under the number of installed wind turbines, to reduce its cost. It is compared the prediction outcome from two different interpolation methods, kriging and radial basis function, assessing their accuracy by the Mean-Squared Error and the Goodness-of-Prediction Estimate, as well as with a visual examination of their mapping; obtaining higher accuracy for radial basis function and reducing to half the required sample points, from the initial value of installed wind turbines. In a second stage it is studied the soil effect over the foundation, analyzing the results from a FEA, where different geometries of the structure are compared submitted to different load cases to check its limit states. Those results show that the foundation cost can increase four times due to the soil conditions, taking into account only the steel volume, and demonstrating how important is the soil characterization in the foundation design, as it gives the chance to relocate those wind turbines that require more expensive foundations.

Single-beam echosounders are an inexpensive, practical and non-invasive means of remote sensing the seabed. Ideally, the common single-beam echosounder should be able to tell fishers, navigators, engineers and scientists what the seabed consists of in addition to water depth. Low-frequency underwater acoustic systems (<10 kHz) can do this in some circumstances, but are expensive, offer limited resolution and potentially hazardous to marine mammals. High-frequency systems, such as single and multibeam echosounders, are very effective at mapping bathymetry, but do not characterize the seabed directly. Instead, these systems divide the seabed into self-similar segments or classes, and then rely on ground-truth data (usually sediment grab samples) to assign seabed-type labels such as sand, etc., to the classes. However, inadequate and inaccurate ground-truth is a major problem. Single-beam seabed classification methods also suffer from a lack of discriminatory power and from artefacts such as water depth and seabed slope. The cause of these problems is that the methods lack a basis in physics and are mainly statistical. Then, the central objective in this dissertation is to develop physics-based methods to improve classification and to address the problem of ground-truth by inferring seabed characteristics directly from the acoustics. An overview of current methods is presented along with case studies of single-beam surveys to introduce the current seabed classification method called QTC VIEW™ and to identify specific problems. A physical basis is established in scattering and geometrical theories and observations of field and model data. This leads to new classification and characterization methods that overcome the shortcomings of current seabed classification methods. Advancements also include new physical models of echosounding. The new methods are presented, implemented and evaluated. Highlights of experimental results include a new testbed located in Patricia Bay, British Columbia. The testbed consists of exhaustive ground-truth, surveys and novel controlled experiments with various single-beam echosounders, ranging in frequency from 12 to 200 kHz. Simulated echo time series data from the numerical BORIS model and a new analytic model are used to augment the testbed. Evaluation of experimental results shows the new physics-based methodology improves seabed classification significantly and enables seabed characterization by an uncalibrated single-beam echosounder. / Graduate