This thesis introduces methods for adding user-guided depth-aware effects to images captured with a consumer-grade stereo camera with minimal user interaction. In particular, we present methods for highlighted depth-of-field, haze, depth-of-field, and image relighting. Unlike many prior methods for adding such effects, we do not assume prior scene models or require extensive user guidance to create such models, nor do we assume multiple input images. We also do not require specialized camera rigs or other equipment such as light-field camera arrays, active lighting, etc. Instead, we use only an easily portable and affordable consumer-grade stereo camera. The depth is calculated from a stereo image pair using an extended version of PatchMatch Stereo designed to compute not only image disparities but also normals for visible surfaces. We also introduce a pipeline for rendering multiple effects in the order they would occur physically. Each can be added, removed, or adjusted in the pipeline without having to reapply subsequent effects. Individually or in combination, these effects can be used to enhance the sense of depth or structure in images and provide increased artistic control. Our interface also allows editing the stereo pair together in a fashion that preserves stereo consistency, or the effects can be applied to a single image only, thus leveraging the advantages of stereo acquisition even to produce a single photograph.

<p>Information about the conditions of specific fields and assets is critical for farm managers to make operational decisions. Location, rainfall, windspeed, soil moisture, and temperature are examples of metrics that influence the ability to perform certain tasks. Monitoring these events in real time and being able to store historical data can be done using Internet of Things (IoT) devices such as sensors. The abilities of this technology have previously been communicated, yet few farmers have adopted these connected devices into their work. A lack of reliable internet connection, the high annual cost of current on-market systems, and a lack of technical awareness have all contributed to this disconnect. One technology that can better meet the demand of farmers is LoRaWAN because of its long range, low power, and low cost. To assist farmers in implementing this technology on their farms the goal was to build a LoRaWAN network with several sensors to measure metrics such as weather data, distribute these systems locally, and provide context to the operation of IoT networks. By leveraging readily available commercial hardware and opens source software two examples of standalone networks were created with sensor data stored locally and without a dependence on internet connectivity. The first use case was a kit consisting of a gateway and small PC mounted to a tripod with 6 individual sensors and cost close to $2200 in total. An additional design was prepared for a micro-computer-based version using a Raspberry Pi, which made improvements to the original design. These adjustments included a lower cost and complication of hardware, software with more open-source community support, and cataloged steps to increase approachability. Given outside factors, the PC architecture was chosen for mass distribution. Over one year, several identical units were produced and given to farms, extension educators, and vocational agricultural programs. From this series of deployments, all units survived the growing season without damage from the elements, general considerations about the chosen type of sensors and their potential drawbacks were made, the practical observed average range for packet acceptance was 3 miles, and battery life among sensors remained usable after one year. The Pi-based architecture was implemented in an individual use case with instructions to assist participation from any experience level. Ultimately, this work has introduced individuals to the possibilities of creating and managing their own network and what can be learned from a reasonably simple, self-managed data pipeline.</p>

Twenty years ago, Chang et al. (1998) introduced the three-yield stresses concept (dynamic, static and elastic limits) to describe yielding of waxy crude oils cooled below the wax appearance temperature (WAT). At the time, the limits in rheological instruments were such that they never actually measured the elastic-limit, a key fundamental property. Using modern instruments, this research succeeds in recording for the first time the entire yielding process down to stresses of 10-7 Pa and shear rate of 10-6 min-1 as a function of temperature, cooling rate and stress loading rate using two waxy oils of different origins and wax content. A four-yield stress model is established using derivative data (dynamic fluidity and failure acceleration). In addition, calorimetry (DSC) and microscopy (CPM) helped extract WAT, the gel and pour points and link gel crystal structure and its yielding and breakage to rheological properties. The yielding stresses measured rheologically were tested in laboratory pipelines at two diameter scales, 6.5mm and 13.5mm to compare stresses in uniform and non-uniform cooling. It is demonstrated that rheological instruments can only predict gel breaking pressure when the cooling rate is low, i.e. yielding at the pipe wall. A complementary heat transfer study was performed on a section of pipe statically cooled, both experimentally and theoretically to predict the gel front-liquid oil interface that develops in industrial pipeline where gel breaking occurs. This key information together with rheological data provide the means to predict accurately restart pressures of shut gelled pipelines that have eluded previous research. / Ministry of Higher Education of the Libyan Government

[pt] A avaliação não destrutiva ultrassônica é de extrema importância na indústria de óleo e gás, principalmente para ativos e estruturas sujeitos a condições que aceleram os mecanismos de falha. Apesar de amplamente difundidos, os métodos ultrassônicos não destrutivos dependem de uma força de trabalho especializada, sendo, portanto, suscetíveis a erros e demorados. Nesse contexto, métodos de reconhecimento de padrões, como o aprendizado de máquina, se encaixam convenientemente para solucionar os desafios da tarefa. Assim, este trabalho tem como objetivo a aplicação de técnicas de inteligência artificial para abordar a interpretação de dados adquiridos por meio de avaliação não destrutiva ultrassônica no contexto da indústria de óleo e gás. Para tanto, esta dissertação envolve três estudos de caso. Primeiramente, sinais de ondas guiadas ultrassônicas são usados para classificar os defeitos presentes em juntas soldadas de compósito termoplástico. Os resultados mostraram que, ao usar atributos extraídos com modelos autoregressivos, a acurácia do modelo de aprendizado de máquina melhora em pelo menos 72,5 por cento. Em segundo lugar, dados ultrassônicos em formato de imagens são usados para construir um sistema de diagnóstico de solda automático. A estrutura proposta resultou em um modelo computacionalmente eficiente, capaz de realizar classificações com acurácia superior à 99 por cento. Por fim, dados obtidos por simulação numérica foram usados para criar um modelo de aprendizado profundo visando estimar a severidade de defeitos semelhantes à corrosão em dutos. Resultados de R2 superiores a 0,99 foram alcançados. / [en] Ultrasonic non-destructive evaluation is of extreme importance in the oil and gas industry, especially for assets and structures subjected to conditions that accelerate failure mechanisms. Despite being widely spread, ultrasonic non-destructive methods depend on a specialized workforce, thus being errorprone and time-consuming. In this context, pattern recognition methods, like machine learning, fit conveniently to solve the challenges of the task. Hence, this work aims at applying artificial intelligence techniques to address the interpretation of data acquired through ultrasonic non-destructive evaluation in the context of the oil and gas industry. For that purpose, this dissertation involves three case studies. Firstly, ultrasonic guided wave signals are used to classify defects present in welded thermoplastic composite joints. Results have shown that, when using features extracted with autoregressive models, the accuracy of the machine learning model improves by at least 72.5 percent. Secondly, ultrasonic image data is used to construct an automatic weld diagnostic system. The proposed framework resulted in a lightweight model capable of performing classification with over 99 percent accuracy. Finally, simulation data was used to create a deep learning model for estimating the severity of corrosion-like defects in pipelines. R2 results superior to 0.99 were achieved.

[pt] Sabe-se que os anéis e tubulações elásticas de paredes finas estão sujeitos a instabilidades quando sob tensões compressivas. Um exemplo particularmente interessante é a flambagem de um anel elástico sob uma pressão hidrostática. A carga de flambagem é fortemente influenciada pela natureza seguidora da força devida à pressão hidrostática e, se esse efeito for desprezado, a previsão da carga de flambagem crítica pode ser de até 50 por cento para anéis esbeltos. Este trabalho estuda, usando uma formulação variacional não linear, as características de flambagem e vibração de anéis e tubulações apoiados em uma fundação elástica de Pasternak, sendo a fundação de Winkler considerada como um caso particular. Primeiro, a equação de movimento do anel pré-carregado é derivada e a solução analítica dos problemas de autovalor é obtida. A análise paramétrica mostra a influência dos parâmetros geométricos e físicos do anel e da fundação na carga crítica, frequências naturais e relação não linear carga-frequência, considerando o efeito da força seguidora da pressão hidrostática. Adicionalmente, o efeito da fundação nas deformações pré-críticas é estudado. Finalmente, o efeito de uma imperfeição geométrica inicial é avaliado usando o método de Galerkin. Os resultados mostram que os parâmetros da fundação de Pasternak têm um efeito considerável na carga e modo crítico, na frequência fundamental do anel. / [en] It is known that thin-walled elastic rings and pipes are subject to instability when under a state of compressive stresses. A particularly interesting example is the buckling of an elastic ring under hydrostatic pressure. The buckling load is strongly influenced by the following nature of the force due to the hydrostatic pressure and, if this effect is neglected, the forecast of the critical buckling load can be up to 50 per cent for slender rings. This work studies, using a non-linear variational formulation, the buckling and vibration characteristics of rings and pipes supported by a Pasternak elastic foundation, the Winkler foundation being considered as a particular case. First, the equation of motion of the preloaded ring is derived and the analytical solution of the eigenvalue problems is obtained. Parametric analysis shows the influence of the geometric and physical parameters of the ring and the foundation on the critical load, natural frequencies and nonlinear load-frequency relationship, considering the force following effect of the hydrostatic pressure. Additionally, the effect of the foundation on pre-critical deformations is studied. Finally, the effect of an initial geometric imperfection is assessed using the Galerkin method. The results show that the parameters of the Pasternak foundation have a considerable effect on the critical load and mode as well as on the natural frequencies of the ring.

Starting with tensor calculus and the variational form of the Hamiltonian functional, a generalized theory is formulated for doubly curved thin shells. The formulation avoids geometric approximations commonly adopted in other formulations. The theory is then specialized for cylindrical and toroidal shells as special cases, both of interest in the modeling of straight and elbow segments of pipeline systems. Since the treatment avoids geometric approximations, the cylindrical shell theory is believed to be more accurate than others reported in the literature. By adopting a set of consistent geometric approximations, the present theory is shown to revert to the well known Flugge shell theory. Another set of consistent geometric approximations is shown to lead to the Donnell-Mushtari-Vlasov (DMV) theory. A general closed form solution of the theory is developed for cylinders under general harmonic loads. The solution is then used to formulate a family of exact shape functions which are subsequently used to formulate a super-convergent finite element. The formulation efficiently and accurately captures ovalization, warping, radial expansion, and other shell behavioural modes under general static or harmonic forces either in-phase or out-of-phase. Comparisons with shell solutions available in Abaqus demonstrate the validity of the formulation and the accuracy of its predictions. The generalized thin shell theory is then specialized for toroidal shells. Consistent sets of approximations lead to three simplified theories for toroidal shells. The first set of approximations has lead to a theory comparable to that of Sanders while the second set of approximation has lead to a theory nearly identical to the DMV theory for toroidal shells. A closed form solution is then obtained for the governing equation. Exact shape functions are then developed and subsequently used to formulate a finite element. Comparisons with Abaqus solutions show the validity of the formulation for short elbow segments under a variety of loading conditions. Because of their efficiency, the finite elements developed are particularly suited for the analysis of long pipeline systems.

No description available.

The box corer is a relatively new tool used in the geotechnical community for collection of soft seabed sediments. Miniature full flow and model pipeline probes were developed as tools to characterize and obtain soil parameters of soft seabed sediments collected in the box core for design of offshore pipelines and analysis of shallow debris flows. Probes specifically developed for this study include the miniature t-bar, ball, motorized vane (MV), and toroid. The t-bar, ball, and MV were developed to measure intact and remolded undrained shear strengths (su and sur). The t-bar and ball can obtain continuous strength profiles and measure sur at discrete depths in the box corer while the MV measures su and sur at discrete depths. The toroid is a form of model pipeline testing which was developed to investigate pipe-soil interaction during axial pipeline movement. Vertical loading and displacement rates can be selected for the toroid to mimic axial pipeline displacement for a variety of pipe weights. A load frame for both miniature penetrometer and toroid testing was developed for testing directly on box core samples offshore. This research presents results from offshore and laboratory testing of the box core and recommended testing procedures for full flow and toroid probes on box core samples.

Диссертация посвящена проблеме возникновения шума и вибрации от трубопроводных систем многоэтажных зданий. Предложен способ определения вероятности возникновения повышенных вибраций с помощью модального анализа в программном комплексеANSYS Workbench. Представлены результаты численного анализа влияния длины, диаметра и толщины стенки участка трубопровода на изменение значений частот его собственных колебаний с целью прогноза риска возможных резонансных режимов. Выполнены статистический и регрессионный анализы. / The dissertation discusses the occurrence of noise and vibration from the piping systems of multi-storey buildings. A method for determining the probability of excessive vibrations using modal analysis software complex ANSYS Workbench. The results of the digital analysis of influence of length, diameter and thickness of a wall of the pipeline’s section on change of values of frequencies of its natural oscillations are provided. Statistical and regression analyses are made.

Sondage post-électoral de l'élection canadienne de 2019 / Ce mémoire vise à comprendre la place que la lutte aux changements climatiques a occupée lors de l’élection fédérale de 2019, considérée par plusieurs comme ayant déterminé par l’attitude des électeurs à propos des changements climatiques. Il analyse la relation entre le comportement électoral et les ramifications climatiques, incarnée par les enjeux de la taxe carbone et les oléoducs, qui clivent la classe politique et qui ont servi d’explication à la suite de la victoire du Parti libéral du Canada de Justin Trudeau. Certains commentateurs politiques – d’Ouest en Est - ont avancé que pour la première fois dans l’histoire canadienne, une élection canadienne a été le théâtre d’un référendum sur les changements climatiques. D’autres ont annoncé le grand gagnant de l’élection ne fût pas tant le gouvernement sortant de Justin Trudeau, et encore moins la formation conservatrice défaite dirigée par Andrew Scheer, mais bien celle de de la taxe carbone adoptée par le gouvernement fédéral dans le Cadre pancanadien sur la croissance propre et les changements climatiques en 2017. / This paper aims to understand the place that the climate change took in the 2019 federal election, considered by many to have determined voters' attitudes to climate change. It analyzes the relationship between electoral behavior and climate ramifications, embodied in the carbon tax and oil pipeline issues that split the political class and served as an explanation for the victory of Justin Trudeau's Liberal Party of Canada. Some political commentators from West to East argued that for the first time in Canadian history, a Canadian election was the scene of a referendum on climate change. Others announced that the big winner of the election was notJustin Trudeau's outgoing government, nor the defeated Conservative formation led by Andrew Scheer, but the carbon tax adopted by the federal government in the 2017 Pan-Canadian Framework on Clean Growth and Climate Change.