This research study developed basic dynamic models that can be used to accurately predict the response behavior of a near-shore wind turbine structure with monopile, suction caisson, or gravity-based foundation systems. The marine soil conditions were modeled using apparent fixity level, Randolph elastic continuum, and modified cone models. The offshore wind turbine structures were developed using a finite element formulation. A two-bladed 3.0 megawatt (MW) and a three-bladed 1.5 MW capacity wind turbine were studied using a variety of design load, and soil conditions scenarios. Aerodynamic thrust loads were estimated using the FAST Software developed by the U.S Department of Energy’s National Renewable Energy Laboratory (NREL). Hydrodynamic loads were estimated using Morison’s equation and the more recent Faltinsen Newman Vinje (FNV) theory. This research study addressed two of the important design constraints, specifically, the angle of the support structure at seafloor and the horizontal displacement at the hub elevation during dynamic loading. The simulation results show that the modified cone model is stiffer than the apparent fixity level and Randolph elastic continuum models. The effect of the blade pitch failure on the offshore wind turbine structure decreases with increasing water depth, but increases with increasing hub height of the offshore wind turbine structure.

The advancement of foundation models have opened up new possibilities in deep learning. These models can be adapted to new tasks and unseen domains from minimal or even no training data, making them well-suited for applications where labelled data is scarce or costly to collect. Lack of data has meant that deep learning for change detection in sonar imagery has not been used. Reliable methods for change detection of underwater environments is critical for a range of fields such as marine research and object search. Previous work in change detection for sonar imagery focus on non-deep learning methods. In this paper, we explore the use of a foundation model (Segment Anything Model) for performing change detection in imagery collected with synthetic aperture sonar (SAS). This thesis is the first case of applying Segment Anything Model to change detection in SAS imagery. The proposed method segments bi-temporal images, and change detection is then performed on the segments. In addition to a set of bi-temporal images containing real change, the model is also tested on a set of synthetic images. The proposed method shows promising results on both a real and synthetic data set.

Thesis (MBA) -- Stellenbosch University, 2006. / ENGLISH ABSTRACT: This study project aims at investigating and selecting the most proficient facilitation tools to propel an organisation towards excellence, based on the theory, principles and practices of the South African Business Excellence Foundation Model (SAEM). It focuses on established and documented processes, models and matrices that can serve as a toolkit for organisations to facilitate excellence through simplification of complex business problems and to provide a visual aid when confronted with every day organisational issues. The study shows that the SAEM is structured model and by using it in conjunction with the various models and matrices it provides a solid foundation for facilitating excellence in business. / AFRIKAANSE OPSOMMING: Hierdie studie identifiseer die modelle en matrikse wat organisasies kan help om 'n vlak van uitmuntendheid te bereik. Die SAEM (South African Excellence Model) word as basis gebruik en die 11 pilare van die SAEM dien as 'n raamwerk vir die ondersoek. Die studie identifiseer slegs die modelle en matrikse wat op deeglike besigheidsbeginsels gegrond is en wat deur erkende navorsers gebruik word om algemene besigheidsprobleme die hoof te bied. Die model en matrikse vereenvoudig die elemente wat vervat is in die SAEM en dien ook as visuele hulpmiddels om sodoende organisasies se strewe na uitmuntendheid te fasiliteer. Die studie toon aan dat die SAEM tesame met die onderskeie modelle en matrikse 'n gestruktueerde benadering bied om organisasies se strewe na uitmuntendheid te fasiliteer.