The Lite (Light) satellite for the study of B-mode polarization and Inflation from cosmic background Radiation Detection (LiteBIRD) is a Japan Aerospace Exploration Agency (JAXA)-led Strategic Large-Class mission designed to search for the existence of the primordial gravitational waves produced during the inflationary phase of the early Universe, through the measurement of their imprint onto the polarization of the Cosmic Microwave Background (CMB). It is an international collaboration, with European Union (EU) operations being coordinated by France. A short study on the merits of 2-dimensional versus 3-dimensional elements in the Finite Element Model (FEM) meshing of basic plates and beams was performed as well as the analysis of two different methods of representing threaded connections in FEM models. Both these activities were in service of the creation of a FEM model of the structure of the contribution of the EU to LiteBIRD: the Medium-High-Frequency Telescope (MHFT). All analysis was done using the Siemens NX software and the Simcenter Nastran solver. This model has passed preliminary quality checks and will be used for future structural analysis intended to verify the integrity of the design, its compliance with JAXA requirements, and to perform screw dimensioning. The results of those analyses will inform possible future design changes or will support the current design. Logistical work on the project was also performed, consisting of the groundwork to initiate an Assembly, Integration and Testing (AIT) plan and an Assembly, Integration and Verification (AIV) plan. This primarily involved the creation of a Model Definition Document, which contained clear and complete descriptions of the different MHFT models to be used throughout project development. The document defines the purpose and components of the models, the dependencies between models, as well as the necessary tests to be performed on each as part of the AIT and AIV process. A list of the structure interfaces was also created, which will contribute to the development of an interface control document.

Two highly effective content-adaptive methods for generating Delaunay mesh models of images, known as IID1 and IID2, are proposed. The methods repeatedly alternate between mesh simplification and refinement, based on the incremental/decremental mesh-generation framework of Adams, which has several free parameters. The effect of different choices of the framework's free parameters is studied, and the results are used to derive two mesh-generation methods that differ in computational complexity. The higher complexity IID2 method generates mesh models of superior reconstruction quality, while the lower complexity IID1 method trades mesh quality in return for a decrease in computational cost. Some of the contributions of our work include the recommendation of a better choice for the growth-schedule parameter of the framework, as well as the use of Floyd-Steinberg error diffusion for the initial-mesh selection. As part of our work, we evaluated the performance of the proposed methods using a data set of 50 images varying in type (e.g., photographic, computer generated, and medical), size and bit depth with multiple target mesh densities ranging from 0.125% to 4%. The experimental results show that our proposed methods perform extremely well, yielding high-quality image approximations in terms of peak-signal-to-noise ratio (PSNR) and subjective visual quality, at an equivalent or lower computational cost compared to other well known approaches such as the ID1, ID2, and IDDT methods of Adams, and the greedy point removal (GPR) scheme of Demaret and Iske. More specifically, the IID2 method outperforms the GPR scheme in terms of mesh quality by 0.2-1.0 dB with a 62-93% decrease in computational cost. Furthermore, the IID2 method yields meshes of similar quality to the ID2 method at a computational cost that is lower by 9-41%. The IID1 method provides improvements in mesh quality in 93% of the test cases by margins of 0.04-1.31 dB compared to the IDDT scheme, while having a similar complexity. Moreover, reductions in execution time of 4-59% are achieved compared to the ID1 method in 86% of the test cases. / Graduate / 0544, 0984, 0537 / marzouki@uvic.ca

The goal of this thesis is to use machine learning methods for datasets of scanned faces and to create a program that allows to explore and edit faces represented as triangle meshes with a number of controls. Firstly we had to reduce dimension of triangle meshes by PCA and then we tried to predict shape of meshes according to physical properties like weight, height, age and BMI. The modeled faces can be used in animation or games.

This paper familiarizes the reader with contingent convertibles and their role in the current financial landscape. A contingent convertible is a security behaving like a bond in normal times, but that converts into equity or is written down in times of turbulence. The paper presents a few existing pricing approaches and introduces an extension to one of these, the equity derivatives approach, by letting the underlying asset follow a jump-diffusion process instead of a standard Geometrical Brownian Motion. The extension requires sophisticated computational techniques in order for the pricing to stay within reasonable time frames. Since market data is sparse and incomplete in this area, the validation of the model is not performed quantitatively, but instead supported by qualitative arguments.

The thesis focuses on creating point cloud and mesh model of chosen intersections and their applications in forensic-engineering praxis. In the first part, we describe a workflow for creating point cloud and mesh model of intersection by digital photogrammetry. In the second part, we applied these at chosen intersections. Which leads us to the comparison of three digital photogrammetric programs which we used to make point clouds and mesh models. At the end of thesis, we use our mesh models in forensic-engineering praxis and we decide about barriers in sign conditions at intersections.

Darbe nagrinėjami barjero pasirinkimo sandorių įkainojimo metodai. Barjero pasirinkimo sandorių išmokos sutampa su įprastinių pasirinkimo sandorių išmokomis, jei išpildoma papildoma barjero sąlyga, kurią reikia įvertinti. Įkainojimui naudojami diskretieji modeliai: binominis ir trinominis, tiriama jų konvergavimas į klasikinę Black-Scholes formulę. Dėl modelio diskretumo ir barjero sąlygos konvergavimas tam tikrais atvejais yra lėtas ir nemonotoniškas. Todėl siūloma pritaikyti adaptyviojo tinklelio algoritmą, smulkinant trinominio medžio tinklelį kritinėse srityse. Šiame darbe pateikiami rezultatai, gauti palyginus barjero pasirinkimo sandorio įkainojimo modelius. / In this paper we consider barrier options pricing models. Barrier options are standard call or put options except that they disappear or appear if the asset price crosses a predeterminant set of fixing dates. Barrier options are priced using continuous state Black-Scholes model and numerical approximation techniques, such as binomial and trinomial. Because of the the barrier condition and discreteness of these models the convergence to Black-Scholes model sometimes is slow. It is offered to apply adaptive mesh model grafting small sections of fine high-resolution lattice onto a tree in trinomial model. In this work we present the comparison of the models with some numerical results for barrier options.

Triangle meshes have become an increasingly popular shape representation. Given the ease of standardization it allows and the proliferation of devices (scanners, range images ) that capture and output shape information as meshes, this representation is now used in applications such as virtual reality, medical imaging, rapid prototyping, digital art and entertainment, simulation and analysis, product design and development. In product development manipulation of mesh models is required in applications such as visualization, analysis, simulation and rapid prototyping. The nature of manipulation of the mesh includes annotation, interactive viewing, slicing, re-meshing, mesh optimization, mesh segmentation, simplification and editing. Of these editing has received the least attention. Mesh model often requires editing either locally or globally based on the application. With the increased use of meshes it is desirable to have formal reasoning tools that enable manipulation of mesh models in product development. The mesh model may contain artifacts like self-intersection, overlapping triangles, inconsistent normal’s of triangles and gaps or holes with or without islands. It is necessary to repair the mesh before further processing the mesh model. An automatic algorithm is proposed to repair and fill arbitrary holes while maintaining curvature continuity across the boundaries of the hole. The algorithm uses slices across the hole to first identify curves that bridge the hole. These curves are then used to find the surface patch that would fill the hole. The proposed algorithm works for arbitrary holes in any mesh model irrespective of the type of underlying surface and is able to preserve features in the mesh model that are missing in the input information. Since editing during product development is mostly feature based, an automatic algorithm to recognize shape features by directly clustering the triangles constituting a feature in a mesh model is proposed. Shape features addressed in the thesis are volumetric features that are associated with either addition or removal of a finite volume. The algorithm involves two steps – isolating features in 2D slices followed by a 3D traversal to cluster all the triangles in the feature. Editing a mesh model mainly implies editing local volumetric features in that model. An automatic algorithm is proposed for parametric editing of volumetric features in the mesh model. The proposed algorithm eliminates the need of original CAD model while manipulating any volumetric feature in the mesh model based on feature parameters. An automatic algorithm to manipulate global shape parameters of the object using the mesh model is developed. Global shape parameters include thickness, drafts and axes of symmetry. As the mesh models do not explicitly carry this information global editing of mesh models (other than for visualization) has not been attempted thus far. This thesis proposes the use of mid-surface to identify and manipulate global shape parameters for a class of objects that are classified as thin walled objects. Mid-curves are first identified on slices of the part and then the mid-surface is obtained from these mid-curves. Results of implementation are presented and discussed along with the scope for future work.

[pt] À medida que o processo de digitalização avança em diversos setores, a criação de modelos digitais 3D torna-se cada vez mais necessária. Normalmente, esses modelos são construídos por designers 3D, exigindo um esforço manual considerável quando o objeto modelado é complexo. Além disso, como o designer não tem uma referência precisa na maioria dos casos, o modelo resultante está sujeito a erros de medição. No entanto, é possível minimizar o esforço de construção e o erro de medição usando técnicas de aquisição 3D e modelos CAD previamente construídos. A saída típica de uma técnica de aquisição 3D é uma nuvem de pontos 3D bruta, que precisa de processamento para reduzir o ruído inerente e a falta de informações topológicas. Os modelos CAD são normalmente usados para documentar um processo de projeto de engenharia, apresentando alta complexidade e muitos detalhes irrelevantes para muitos processos de visualização. Portanto, dependendo da aplicação, devemos simplificar bastante o modelo CAD para atender aos seus requisitos. Nesta tese, nos concentramos na construção de modelos digitais 3D a partir dessas fontes. Mais precisamente, apresentamos um conjunto de algoritmos de processamento de geometria para automatizar diferentes etapas de um fluxo de trabalho típico usado para esta construção. Primeiro, apresentamos um algoritmo de redução de ruído de nuvem de pontos que visa preservar as feições nítidas da superfície subjacente. Este algoritmo inclui soluções para a estimativa normal e problemas de detecção de feições nítidas. Em segundo lugar, apresentamos uma extensão do algoritmo de redução de ruído de nuvem de pontos para processar malhas triangulares, onde tiramos proveito da topologia explícita definida pela malha. Por fim, apresentamos um algoritmo para a simplificação extrema de modelos CAD complexos, que tendem a se aproximar da superfície externa do objeto modelado. Os algoritmos propostos são comparados com métodos de última geração, apresentando resultados competitivos e superando-os na maioria dos casos de teste. / [en] As the digitalization process advances in several industries, the creation of 3D digital models is becoming more and more required. Commonly, these models are constructed by 3D designers, requiring considerable manual effort when the modeled object is complex. In addition, since the designer does not have an accurate reference in most cases, the resulting model is prone to measurement errors. However, it is possible to minimize the construction effort and the measurement error by using 3D acquisition techniques and previously constructed CAD models. The typical output of a 3D acquisition technique is a raw 3D point cloud, which needs processing to reduce the inherent noise and lack of topological information. CAD models are typically used to document an engineering design process, presenting high complexity and too many details irrelevant to many visualization processes. So, depending on the application, we must severely simplify the CAD model to meet its requirements. In this thesis, we focus on the construction of 3D digital models from these sources. More precisely, we present a set of geometry processing algorithms to automatize different stages of a typical workflow used for this construction. First, we present a point cloud denoising algorithm that seeks to preserve the sharp features of the underlying surface. This algorithm includes solutions for the normal estimation and sharp feature detection problems. Second, we present an extension of the point cloud denoising algorithm to process triangle meshes, where we take advantage of the explicit topology defined by the mesh. Finally, we present an algorithm for the extreme simplification of complex CAD models, which tends to approximate the outer surface of the modeled object. The proposed algorithms are compared with state-of-the-art methods, showing competitive results and outperforming them in most test cases.

本文目的在運用Adaptive Mesh Model，以具有高解析度的細網結構(fine mesh)來評價重設選擇權，以解決傳統Ritchken(1995) 樹狀模型在運用上會出現一些無法有效率運算和收斂狀況不佳二個問題。 本文的貢獻在發現評價重設選擇權可以使用下降生效界限選擇權的原理來探討。另外為解決上述Ritchken模型所面臨的二個問題，應用Adaptive Mesh Model於下生效界限選擇權，設置適當之細網結構，演算出更精確的重設選擇權價格。而且本樹網模型不再受限於美式下出界選擇權與美式下生效界限選擇權的組合不一定是美式重設選擇權的困擾。故在納入Adaptive Mesh Model的下降生效界限選擇權來評價歐式或美式重設選擇權，可以獲得良好的收斂效率。

Corrosion damage reduces the load-carrying capacity of bridges which poses a threat to passenger safety. The objective of this research was to reduce the resources involved in conventional bridge inspections which are an important tool in the condition assessment of bridges and to help in determining if live load testing is necessary. This research proposes a framework to link semi-automated damage detection on prestressed concrete bridge girders with the estimation of their residual flexural capacity. The framework was implemented on four full-scale corrosion damaged girders from decommissioned bridges in Virginia. 3D point clouds of the girders reconstructed from images using Structure from Motion (SfM) approach were textured with images containing cracks detected at pixel level using a U-Net (Fully Convolutional Network). Spalls were detected by identifying the locations where normals associated with the points in the 3D point cloud deviated from being perpendicular to the reference directions chosen, by an amount greater than a threshold angle. 3D textured mesh models, overlaid with the detected cracks and spalls were used as 3D damage maps to determine reduced cross-sectional areas of prestressing strands to account for the corrosion damage as per the recommendations of Naito, Jones, and Hodgson (2011). Scaling them to real-world dimensions enabled the measurement of any required dimension, eliminating the need for physical contact. The flexural capacities of a box beam and an I-beam estimated using strain compatibility analysis were validated with the actual capacities at failure sections determined from four destructive tests conducted by Al Rufaydah (2020). Along with the reduction in the cross-sectional areas of strands, limiting the ultimate strain that heavily corroded strands can develop was explored as a possible way to improve the results of the analysis. Strain compatibility analysis was used to estimate the ultimate rupture strain, in the heavily corroded bottommost layer prestressing strands exposed before the box beam was tested. More research is required to associate each level of strand corrosion with an average ultimate strain at which the corroded strands rupture. This framework was found to give satisfactory estimates of the residual strength. Reduction in resources involved in current visual inspection practices and eliminating the need for physical access, make this approach worthwhile to be explored further to improve the output of each step in the proposed framework. / Master of Science / Corrosion damage is a major concern for bridges as it reduces their load carrying capacity. Bridge failures in the past have been attributed to corrosion damage. The risk associated with corrosion damage caused failures increases as the infrastructure ages. Many bridges across the world built forty to fifty years ago are now in a deteriorated condition and need to be repaired and retrofitted. Visual inspections to identify damage or deterioration on a bridge are very important to assess the condition of the bridge and determine the need for repairing or for posting weight restrictions for the vehicles that use the bridge. These inspections require close physical access to the hard-to-reach areas of the bridge for physically measuring the damage which involves many resources in the form of experienced engineers, skilled labor, equipment, time, and money. The safety of the personnel involved in the inspections is also a major concern. Nowadays, a lot of research is being done in using Unmanned Aerial Vehicles (UAVs) like drones for bridge inspections and in using artificial intelligence for the detection of cracks on the images of concrete and steel members. Girders or beams in a bridge are the primary longitudinal load carrying members. Concrete inherently is weak in tension. To address this problem, High Strength steel reinforcement (called prestressing steel or prestressing strands) in prestressed concrete beams is pre-loaded with a tensile force before the application of any loads so that the regions which will experience tension under the service loads would be subjected to a pre-compression to improve the performance of the beam and delay cracking. Spalls are a type of corrosion damage on concrete members where portions of concrete fall off (section loss) due to corrosion in the steel reinforcement, exposing the reinforcement to the environment which leads to accelerated corrosion causing a loss of cross-sectional area and ultimately, a rupture in the steel. If the process of detecting the damage (cracks, spalls, exposed or severed reinforcement, etc.) is automated, the next logical step that would add great value would be, to quantify the effect of the damage detected on the load carrying capacity of the bridges. Using a quantified estimate of the remaining capacity of a bridge, determined after accounting for the corrosion damage, informed decisions can be made about the measures to be taken. This research proposes a stepwise framework to forge a link between a semi-automated visual inspection and residual capacity evaluation of actual prestressed concrete bridge girders obtained from two bridges that have been removed from service in Virginia due to extensive deterioration. 3D point clouds represent an object as a set of points on its surface in three dimensional space. These point clouds can be constructed either using laser scanning or using Photogrammetry from images of the girders captured with a digital camera. In this research, 3D point clouds are reconstructed from sequences of overlapping images of the girders using an approach called Structure from Motion (SfM) which locates matched pixels present between consecutive images in the 3D space. Crack-like features were automatically detected and highlighted on the images of the girders that were used to build the 3D point clouds using artificial intelligence (Neural Network). The images with cracks highlighted were applied as texture to the surface mesh on the point cloud to transfer the detail, color, and realism present in the images to the 3D model. Spalls were detected on 3D point clouds based on the orientation of the normals associated with the points with respect to the reference directions. Point clouds and textured meshes of the girders were scaled to real-world dimensions facilitating the measurement of any required dimension on the point clouds, eliminating the need for physical contact in condition assessment. Any cracks or spalls that went unidentified in the damage detection were visible on the textured meshes of the girders improving the performance of the approach. 3D textured mesh models of the girders overlaid with the detected cracks and spalls were used as 3D damage maps in residual strength estimation. Cross-sectional slices were extracted from the dense point clouds at various sections along the length of each girder. The slices were overlaid on the cross-section drawings of the girders, and the prestressing strands affected due to the corrosion damage were identified. They were reduced in cross-sectional area to account for the corrosion damage as per the recommendations of Naito, Jones, and Hodgson (2011) and were used in the calculation of the ultimate moment capacity of the girders using an approach called strain compatibility analysis. Estimated residual capacities were compared to the actual capacities of the girders found from destructive tests conducted by Al Rufaydah (2020). Comparisons are presented for the failure sections in these tests and the results were analyzed to evaluate the effectiveness of this framework. More research is to be done to determine the factors causing rupture in prestressing strands with different degrees of corrosion. This framework was found to give satisfactory estimates of the residual strength. Reduction in resources involved in current visual inspection practices and eliminating the need for physical access, make this approach worthwhile to be explored further to improve the output of each step in the proposed framework.