No description available.

No description available.

The multiangle submerged jet test device (JTD) provides a simple in situ method of measuring streambank critical shear stress (Ï c) and soil erodibility (kd). Previous research showed streambank kd and Ï c can vary by up to four orders of magnitude at a single site; therefore, it is essential to determine if the large range is due to natural variability in soil properties or errors due to the test method. The study objectives were to evaluate the repeatability of the JTD and determine how it compares to traditional flume studies. To evaluate the repeatability, a total of 21 jet tests were conducted on two remolded soils, a clay loam and clay, compacted at uniform moisture content to a bulk density of 1.53 g/cm^3 and 1.46 g/cm^3, respectively. To determine the similarity between JTD and a traditional measurement method, JTD Ï c and kd measurements were compared with measurements determined from flume tests. The JTD kd and Ï c ranged from 1.68-2.81 cm³/N-s and 0.28-0.79 Pa, respectively, for the clay loam and 1.36-2.69 cm³/N-s and 0.30-2.72 Pa, respectively, for the clay. The modest variation of kd and Ï c for the remolded soils suggests the JTD is repeatable, indicating the wide range of parameters measured in the field was a result of natural soil variability. The JTD median kd and Ï c, except clay loam kd (clay loam kd = 2.31 cm^3/N-s, Ï c = 0.45 Pa; clay kd = 2.18 cm^3/N-s, Ï c = 1.10 Pa) were significantly different than the flume values (clay loam kd = 2.43 cm³/N-s, Ï c = 0.23 Pa; clay kd = 4.59 cm³/N-s, Ï c = 0.16 Pa); however, considering the range of potential errors in both test methods, the findings indicate the multiangle submerged jet test provides reasonable measurement of erosion parameters in a field setting. / Master of Science

Estimates of bank erosion typically require field measurements to determine the soil erodibility since soil characteristics are highly variable between sites, especially for cohesive soils. The submerged jet test device is an in situ method of determining the critical shear stress and soil erodibility of cohesive soils. A constant velocity jet, applied perpendicular to the soil surface, creates a scour hole which is measured at discrete time intervals. While the results of these tests are able to provide values of critical shear stress and soil erodibility, the results are often highly variable and do not consider certain aspects of scour phenomena found in cohesive soils. Jet test measurements taken on the lower Roanoke River showed that the results varied for samples from similar sites and bulk failures of large areas of soil were common on the clay banks. Computational Fluid Dynamics (CFD) can be used to determine the effect of scour hole shape changes on the applied shear stress. Previous calculation methods assumed that the depth of the scour hole was the only parameter that affected the applied shear stress. The analysis of the CFD models showed that depth did heavily influence the maximum shear stress applied to the soil boundary. However, the scour hole shape had an impact on the flow conditions near the jet centerline and within the scour hole. Wide, shallow holes yielded results that were similar to the flat plate, therefore it is recommended that field studies only use jet test results from wide, shallow holes to determine the coefficient of erodibility and the critical shear stress of cohesive soils. / Master of Science

The entrainment process in two-phase buoyant jets differs significantly from their singlephase counterparts, and is not well understood. Entrainment models developed for singlephase flow are often used in two-phase jetting simulations, albeit with limited success. In this work, Particle Image Velocimetry (PIV) and shadowgraph flow visualization experiments have been conducted on submerged round gas jets of varying speeds and nozzle diameters with the goal of improving our understanding of the entrainment process in a two-phase (gas-liquid) jet. The total entrainment estimated using the PIV measurements is higher than the respective values suggested by a common empirical model developed for singlephase buoyant jets. A two-phase theoretical entrainment model used for comparison shows an overestimation of entrainment, but predicts the increase in the rate of entrainment with axial distance from the jet nozzle seen in the PIV results. This thesis also presents advances in PIV processing methodology that were developed concurrently with the entrainment research. The novel Spectral Phase Correlation (SPC) allows for particle displacement to be determined directly from phase information in the Fourier domain. Some of the potential benefits of the SPC explored here include (1) avoidance of errors introduced by spatial peak-finding routines; (2) use of a modal analysis that can be used to provide information such as correlation quality; and (3) introduction of a means of incorporating information from multiple image windows. At low image noise levels, the method performs as well as an advanced CC-based method. However, difficulties unwrapping the aliased phase information cause the SPC's performance to degrade at high noise levels. / Master of Science

The objective of this thesis is the algorithmic enhancement and initial evaluation of an underwater acoustic positioning system which is designed to determine the position and orientation of a mobile nuclear reactor vessel inspection robot. Although a great deal of research has been done in the area of underwater acoustic positioning, this work differs from previous work in three significant ways. First, most applied acoustic positioning systems have been designed for the offshore oil drilling industry, and thus their requirements and restrictions are dictated by an oceanic environment. Second, most previous work has focused only upon acquiring the position of a point from the acoustic system. The inspection robot operation requires accurate positioning and orientation. Finally, the accuracy of acoustic positioning systems is generally dependent upon an evaluation of the speed of sound. However, this parameter is highly dependent upon water temperature. As will be discussed, the reactor vessel water temperature may not be uniform or constant, which makes the design of a precise positioning system difficult. Original methods to overcome this obstacle are discussed and evaluated. Also examined are configurations and constraints of the acoustic transceivers, the numerical solution procedures utilized, and the resulting errors associated with the developed methods. / Master of Science

In this dissertation, an approach for determining parameters for a nonlinear Lagrangian mechanical system model of a submerged vessel maneuvering near waves is presented. The nonlinear model with determined parameters is capable of capturing nonlinear effects neglected by other linear models, and therefore can be applied to improve maneuvering performance and expand the operating envelope for submerged vessels operating in elevated sea states. To begin, a first principles Lagrangian nonlinear maneuvering (LNM) model for a surface-affected submerged vessel derived by using Lagrangian mechanics cite{BattistaPhD2018} is reformulated to allow the application of data from a medium fidelity potential flow code. In the reformulation process, the order of integration and differentiation in the integro-differential parameters are switched and partial derivatives of the Lagrangian function are computed with readily available data from the panel code solution. As a result, all model parameters can be computed individually using the panel code, wherein the need for additional numerical discretization is circumvented in the computation process through use of solutions already performed by the basic panel code, enabling higher accuracy and lower computational cost. Furthermore, incident wave effects are incorporated into the reformulated LNM model to yield a Lagrangian nonlinear maneuvering and seakeeping (LNMS) model. The LNMS model is numerically validated by confirming the proposed methods and by comparing steady and unsteady hydrodynamic force calculations from the LNMS model against panel code computations for various vessel motions in calm water and in plane progressive waves. Finally, methods for computing physically intuitive components of the model parameters, as well as methods for making approximations of the terms accounting for memory effects are presented, leading to a model formulation amenable to control design. By applying the methods proposed in this dissertation, each and every parameter of the Lagrangian mechanical system model of a submerged vessel maneuvering in waves can be obtained accurately and with computational efficiency by using a potential flow panel code. The resulting nonlinear motion model provides higher model fidelity than existing unified maneuvering and seakeeping models, especially in applications such as nonlinear control design and simulation. / Doctor of Philosophy / A unified maneuvering and seakeeping model for a submerged vessel maneuvering near waves describes mathematically the relationship between input values to the dynamical system, such as thrust from the propulsors, and output values from the system, such as the position and orientation of the vessel. This unified model has a wide range of applications, ranging from vessel hull form optimization in the early design phase to motion controller tuning after the vessel has been constructed. In order for a unified model to make accurate predictions, for instance, for a submerged vessel making a rapid turn near large waves, nonlinear effects have to be included in the model formulation. To that end, a nonlinear motion model for a marine craft affected by a free surface has been developed using Lagrangian mechanics. This dissertation describes an approach for determining the parameters of the nonlinear motion model using a potential flow panel code, which is originally designed to determine flow velocity of the fluid and pressure distribution over marine vessels. The nonlinear motion model is reformulated and the software implementation is modified to support parameter computations. In addition, the methods are numerically validated by comparing computations using the model against solutions output by the panel code. Compared to traditional parameter estimation approaches, the proposed methods allow for a more accurate and efficient determination of parameters of the nonlinear potential flow model for a submerged vessel operating near waves. The resulting Lagrangian nonlinear maneuvering and seakeeping (LNMS) model with determined parameters is able to capture critical nonlinear effects and has applications such as nonlinear control design, rapid design optimization and training simulator development.

Better understanding of the role of vegetation in the transport of fluid and pollutants requires improved knowledge of the detailed flow structure within the vegetation. Instead of spatial averaging, this study uses discrete measurements at multiple locations within the canopy to develop velocity and turbulence intensity profiles and observe the changes in the flow characteristics as water travels through a vegetation array simulated by rigid dowels. Velocity data were collected with a one dimensional laser Doppler velocimeter (LDV) under single layer emergent and submerged flow conditions, and through two layers of vegetation. The effects of dowel arrangement, density, and roughness are also examined under the single layer experiments. The results show that the velocity within the vegetation array is constant with depth and the velocity profile is logarithmic above it. The region immediately behind a dowel, where the vorticity and turbulence intensity are highest, is characterized by a velocity spike near the bed and an inflection point near the top of the dowel arrays. With two dowel layers, the velocity profile in the region behind a tall dowel exhibits multiple inflection points and the highest turbulence intensities are found there. / Master of Science

Investigating the archaeology of submerged landscapes beneath many metres of sea and buried under modern sands requires an understanding of the terrestrial surface as it may have been prior to the inundation. To do this, environmental evidence is required from contextualised in-situ locations and the best material evidence for preservation of archaeology, organic remains, dating proxies, pollen, diatoms, microfossils, coleoptera etc. is peat. This research supports the search for peat in submarine environments by interpreting seismic surveys of the sub-sea floor and analysing reflective signals for distinctive organic responses. By means of sedimental analysis and ground observation, the research sets out to differentiate between organic signals, to allow for the identification and location of shallow peat beds within features of a palaeolandscape. Using these results should provide an opportunity to target such peat beds in an archaeologically focused coring programme. The research also examines ways in which organic responses may be mapped over larger areas in order to integrate the results into a wider scale landscape model identifying potential peatland, marsh, valley fen and lowland areas. Finally, the research introduces an artificial intelligence neural networking technology for the identification of organic interfaces in seismic surveys, examining three different ways in which this could be accomplished using specialist computer tools and software.

Yes / The value of artificial intelligence and machine learning applications for use in heritage research is increasingly appreciated. In specific areas, notably remote sensing, datasets have increased in extent and resolution to the point that manual interpretation is problematic and the availability of skilled interpreters to undertake such work is limited. Interpretation of the geophysical datasets associated with prehistoric submerged landscapes is particularly challenging. Following the Last Glacial Maximum, sea levels rose by 120 m globally, and vast, habitable landscapes were lost to the sea. These landscapes were inaccessible until extensive remote sensing datasets were provided by the offshore energy sector. In this paper, we provide the results of a research programme centred on AI applications using data from the southern North Sea. Here, an area of c. 188,000 km2 of habitable terrestrial land was inundated between c. 20,000 BP and 7000 BP, along with the cultural heritage it contained. As part of this project, machine learning tools were applied to detect and interpret features with potential archaeological significance from shallow seismic data. The output provides a proof-of-concept model demonstrating verifiable results and the potential for a further, more complex, leveraging of AI interpretation for the study of submarine palaeolandscapes.