published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

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No description available.

Texture evolution of depleted uranium is investigated using a viscoplastic self-consistent model. Depleted uranium, which has the same structure as alpha-uranium, is difficult to model as it has an orthorhombic symmetry structure, as well as many twin systems which must be addressed in order to properly simulate the textural evolution. The VPSC method allowed for a flexible model which could not only encompass the low symmetry component but also the twinning components of depleted uranium. The model focuses on the viscoplastic regime only, neglecting the elastic regime of deformation, and uses a self-consistent method to solve the model. Different deformation processes, such as torsion, rolling, and swaging, are simulated and the theoretical textures, plotted as pole figures or inverse pole figures, are compared with previous experimental textures found for alpha uranium from previous experimental sources. A specific twin system, the (176)[512] system, is also given special consideration. This twin system is a dominant deformation mode for alpha uranium at high strain rates, but is quite elusive in general. Different deformation processes are compared where this twin system is active and not active. This allows comparison on the effect of this twin on the overall texture of depleted uranium. In addition, a sample of depleted uranium from Y12 which was analyzed for (176)[512] twins is compared to theoretical results from a VPSC simulation where the (176)[512] twin is active.

[Truncated abstract] One common task in Computer Vision is the estimation of three-dimensional surface shape from two-dimensional images. This task is important as a precursor to higher level tasks such as object recognition - since shape of an object gives clues to what the object is - and object modelling for graphics. Many visual cues have been suggested in the literature to provide shape information, including the shading of an object, its occluding contours (the outline of the object that slants away from the viewer) and its appearance from two or more views. If the image exhibits a significant amount of texture, then this too may be used as a shape cue. Here, ‘texture’ is taken to mean the pattern on the surface of the object, such as the dots on a pear, or the tartan pattern on a tablecloth. This problem of estimating the shape of an object based on its texture is referred to as shape-form-texture and it is the subject of this thesis . . . The work in this thesis is likely to impact in a number of ways. The second shape-form-texture algorithm provides one of the most general solutions to the problem. On the other hand, if the assumptions of the first shape-form-texture algorithm are met, this algorithm provides an extremely usable method, in that users should be able to input images of textured objects and click on the frontal texture to quickly reconstruct a fairly good estimation of the surface. And lastly, the algorithm for estimating the transformation between textures can be used as a part of many shape-form-texture algorithms, as well as being useful in other areas of Computer Vision. This thesis gives two examples of other applications for the method: re-texturing an object and placing objects in a scene.