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The Global ETD Search service is a free service for researchers
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Showing 21 to 22 of 22 (0.051 seconds)Spelling suggestions: "subject:"allocation"" "subject:"dislocation""
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Co-located offshore wind and tidal stream turbinesLande-Sudall, David January 2017 (has links)
Co-location of offshore wind turbines at sites being developed for tidal stream arrays has been proposed as a method to increase capacity and potentially reduce the cost of electricity compared to operating either technology independently. This research evaluates the cost of energy based on capital expenditure and energy yield. It is found that, within the space required around a single 3 MW wind turbine, co-location provides a 10-16% cost saving compared to operating the same size tidal-only array without a wind turbine. Furthermore, for the same cost of electricity, a co-located farm could generate 20% more yield than a tidal-only array. These results are based on analysis of a case-study site in the Pentland Firth. Wind energy is assessed using an eddy viscosity wake model in OpenWind, with a 3 MW rated power curve and thrust coefficient from a Vestas V90 turbine. Three years of wind resource data is from the UK Met Office UK Variable (UKV) 1.5 km numerical model and corrected against a 400 m Weather Research and Forecasting (WRF) model run over the site. Tidal stream energy is modelled using a semi-empirical superposition of self-similar plane wakes, with a generic 1 MW rated power curve and thrust based on a full-scale, fixed-pitch turbine. Coincident tidal resource data is from the Forecasting Ocean Assimilation Model (FOAM) at 7.5 km resolution and correlated with a 150 m ADvanced CIRCulation model (ADCIRC). Wave parameters are corrected from ERA-Interim data with six months of wave buoy data. Multiple tidal turbine array layouts are considered, with maximum tidal energy generated for a staggered array with spacing of 20 tidal turbine diameters, Dt , streamwise and 1.5Dt cross-stream. However, cheapest cost of electricity from the tidal-only array, was found for a single row of turbines, due to minimal wake effects. Laboratory experiments were undertaken to validate the superposition wake model for use with large, shared support structures. Two rotors mounted either side of a central tower generate a peak wake velocity deficit 70% greater than predicted by superposition. This was due to high local blockage and a complex near-wake structure, with a corresponding increase in tower drag of 9%. Further experiments evaluated the impact of oblique inflow on turbines yawed at +/-15 degrees. These results validated a theoretical cosine correction for thrust coefficient and characterised the centreline wake drift with downstream distance. Extreme environmental loads for a shared support structure, compared to structures for wind-only and tidal-only, have also been modelled. A non-linear wave model was used to represent a single wave form with 1% occurrence for each hour of time-series data. Overturning moment about the base of a shared support, with one wind and two tidal turbines, was found to be 4.5% larger than for a wind-only turbine in strong current and with turbines in different operational states. Peak loads across the tidal array were found to vary by 2.5% and so little load reduction benefit could be gained by locating a shared support in a more sheltered area of the array.
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Implementation and Analysis of Co-Located Virtual Reality for Scientific Data VisualizationJordan M McGraw (8803076) 07 May 2020 (has links)
<div>Advancements in virtual reality (VR) technologies have led to overwhelming critique and acclaim in recent years. Academic researchers have already begun to take advantage of these immersive technologies across all manner of settings. Using immersive technologies, educators are able to more easily interpret complex information with students and colleagues. Despite the advantages these technologies bring, some drawbacks still remain. One particular drawback is the difficulty of engaging in immersive environments with others in a shared physical space (i.e., with a shared virtual environment). A common strategy for improving collaborative data exploration has been to use technological substitutions to make distant users feel they are collaborating in the same space. This research, however, is focused on how virtual reality can be used to build upon real-world interactions which take place in the same physical space (i.e., collaborative, co-located, multi-user virtual reality).</div><div><br></div><div>In this study we address two primary dimensions of collaborative data visualization and analysis as follows: [1] we detail the implementation of a novel co-located VR hardware and software system, [2] we conduct a formal user experience study of the novel system using the NASA Task Load Index (Hart, 1986) and introduce the Modified User Experience Inventory, a new user study inventory based upon the Unified User Experience Inventory, (Tcha-Tokey, Christmann, Loup-Escande, Richir, 2016) to empirically observe the dependent measures of Workload, Presence, Engagement, Consequence, and Immersion. A total of 77 participants volunteered to join a demonstration of this technology at Purdue University. In groups ranging from two to four, participants shared a co-located virtual environment built to visualize point cloud measurements of exploded supernovae. This study is not experimental but observational. We found there to be moderately high levels of user experience and moderate levels of workload demand in our results. We describe the implementation of the software platform and present user reactions to the technology that was created. These are described in detail within this manuscript.</div>
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