This thesis details work carried out by two students working as contractors at the Community Coordinated Modelling Center at Goddard Space Flight Center of the National Aeronautics and Space Administration. The thesis is made possible by and aims to contribute to the OpenSpace project. The first track of the work implemented is the handling of and putting together new data for a visualization of coronal mass ejections in OpenSpace. The new data allows for observation of coronal mass ejections at their origin by the surface of the Sun, whereas previous data visualized them from 30 solar radii out from the Sun and outwards. Previously implemented visualization techniques are used together to visualize different volume data and fieldlines, which together with a synoptic magnetogram of the Sun gives a multi-layered visualization. The second track is an experimental implementation of a generalized and less user involved process for getting new data into OpenSpace, with a priority on volume data as that was a subject of experience. The results show a space weather model visualization, and how one such model can be adapted to fit within the parameters of the OpenSpace project. Additionally, the results show how a GUI connected to a series of background events can form a data pipeline to make complicated space weather models more easily available.

As part of recognizing the interconnected nature of different sectors in relation to health, AMR (antimicrobial resistance) has emerged as an issue of high global importance. E. coli isolates were taken from pig farms in Thailand, which serves as a point of interest in the study of ARGs (antimicrobial resistance genes) in emerging economies. The fecal samples were collected from pigs, humans who came in contact with the pigs, and humans who did not have contact with pigs to be analyzed for ARGS, virulence genes, and plasmids. Data was analyzed with an automated pipeline in the form of ARG-MATEE, the Antimicrobial Resistance Gene Multi-Analysis Tool for Enteric E. coli, a tool designed in this study to be used here and in future investigations. ARG-MATEE regulates and records internal software versions in a produced report which also includes data tables for all non phylogeny results in Boyce–Codd normal form and data visualizations for plasmids, ARGs, virulence genes, and phylogeny. Through the use of ARG-MATEE, the iss virulence gene was seen to be significantly different between testing groups as it is present in only human testing groups, suggesting the loss of function of the iss gene in pigs, showing host specialization.

This thesis deals with problems of electricity generation and saving at compression stations of magistral gas transporting pipelines in Russia. Russia is a biggest country in the world which faces set of challenges like transporting gas in European part from far North. Average gas travel distance in Russia is over 4000 km which means huge energy demand for transportation. Permanent availability of energy at compression stations is the key for stabile operation of gas transporting system. For satisfying those needs external sources of electricity used, or part of the transported gas used on special “self needs electricity stations” for electricity production. In 2012 in Russia about 655 bln m3 of gas were produced. About 10% of that number doesn’t come to consumer, because this amount spent for gas transport needs (biggest share is electricity production).  It is obvious, that in order to increase income, company should work on transport cost decreasing and on cheap electricity production. Even 10% decrease in transport costs can give economy in about 6-7 bln m3, which is bigger that production of many countries. In this thesis pipeline systems efficiency and reliability, gas turbines in Russian pipeline systems considered. Analysis of renewable energy included and propositions for reconstruction of CS “Russkaya” with help of PV panels for electricity generation and gas usage decreasing included. Also, economical calculations and sensitivity analysis and technological calculation of PV panels installed included. Finally, proposition in area of principal construction of PV panels in hard relief situations on the Black Sea Russian shore included.

Increasingly growing consumption of natural gas all around the world requires development of new transporting equipment and optimization of existing pipelines and gas pumping facilities. As a special case, Russian gas pumping system has the longest pipes with large diameter, which carry great amounts of natural gas. So, as reconstruction and modernization needs large investments, a need of more effective and low cost tool appeared. As a result diagnostics became the most wide-spread method for lifecycle assessment, and lifecycle extension for gas pumping units and pipelines.One of the most effective method for diagnostics of gas pumping units is parametric diagnostics. It is based on evaluation of measurement of several termo-gas dynamic parameters of gas pumping units, such as pressures, temperatures and rotational speed of turbines and compressors.In my work I developed and examined a special case of parametric diagnostics – methodic for evaluation of technical state and output parameters for gas pumping unit “Ural-16”. My work contains detailed analysis of various defects, classified by different GPU’s systems. The results of this analysis are later used in development of the methodic for calculation of output parameters for gas pumping unit.GPU is an extremely complex object for diagnostics. Around 200 combinations of Gas Turbine engines with centrifugal superchargers, different operational conditions and other aspects require development of separate methodic almost for each gas pumping unit type.Development of each methodic is a complex work which requires gathering of all possible parametric and statistical data for the examined gas pumping unit. Also parameters of compressed gas are measured. Thus as a result a number of equations are formed which finally allow to calculate such parameters as efficiency, fuel gas consumption and technical state coefficient which couldn’t be measured directly by existing measuring equipment installed on the gas compressor station.

[pt] O Brasil possui uma já extensa malha offshore de gasodutos e, no desenvolvimento da produção do Pré-Sal, esta deve continuar se expandindo em razão das necessidades de aumento da capacidade de escoamento de gás e também da sua reinjeção nos próprios reservatórios (seja apenas como descarte ou como um método de recuperação avançado). Uma vez instalada, esta malha deve ser periodicamente passar por manutenção, o que implica em eventos esporádicos de esvaziamento destes dutos, normalmente operando a altas pressões. Devido ao custo elevado de tais operações, deve-se estimar com boa precisão o tempo total necessário para despressurização, que pode levar várias horas ou até dias. Além disso, também é importante a previsão do inventário de líquido remanescente nos dutos após a despressurização. No presente trabalho, foi desenvolvido um modelo numérico para prever a despressurização de gasodutos considerando escoamento bifásico homogêneo e unidimensional. A formação e o consumo de condensado é obtida a partir de um inventário inicial de fluido supercrítico, com premissa de equilíbrio entre as fases. As propriedades termodinâmicas dos fluidos são determinadas utilizando-se pacotes comerciais e pré-tabuladas em função de pressão e temperatura. As equações de conservação foram discretizadas pelo método das diferenças finitas, utilizando o método de Euler implícito para o termo temporal e aproximação upwind nas derivadas espaciais. O sistema algébrico resultante foi resolvido diretamente de forma acoplada. Os resultados obtidos mostram boa concordância ao compará-los a dados reais de campo e resultados de simuladores comerciais de referência. / [en] Although Brazilian gas pipeline grid is already quite extensive, it continues to expand due to the Pre Salt development, since there is a growing need to increase the flowing capacity towards onshore facilities and injection wells (gas to be discarded or used for advanced oil recovery). Once pipelines are installed, maintenance operation must be performed quite often to guarantee process efficiency. Usually these operations demand depressurization from very high pressures. Considering the costs involved in such operations it is mandatory to accurately predict the total time for a complete blowdown, which may take several hours or even a couple of days. Furthermore, it is also important to evaluate the condensate content in the pipeline after the depressurization event. In the present work, a numerical model was developed to simulate gas pipeline depressurization considering unidimensional two-phase homogeneous flow. The formation and consumption of condensate from an initial supercritical state is obtained assuming phase equilibrium. Fluid properties are taken from tables generated by PVT packages. Conservation equations are discretized through the finite difference method employing Euler implicit approximation for the time derivatives and upwind scheme for spatial terms. A coupled direct algorithm was adopted to solve the resulting algebraic system. The results are compared to real field data and commercial software showing good agreement.

No description available.

[EN] Over time, due to multiple operational and maintenance activities, the networks of water supply systems (WSSs) undergo interventions, modifications or even are closed. In many cases, these activities are not properly registered. Knowledge of the paths and characteristics (status and age, etc.) of the WSS pipes is obviously necessary for efficient and dynamic management of such systems. This problem is greatly augmented by considering the detection and control of leaks. Access to reliable leakage information is a complex task. In many cases, leaks are detected when the damage is already considerable, which brings high social and economic costs. In this sense, non-destructive methods (e.g., ground penetrating radar - GPR) may be a constructive response to these problems, since they allow, as evidenced in this thesis, to ascertain paths of pipes, identify component characteristics, and detect primordial water leaks. Selection of GPR in this work is justified by its characteristics as non-destructive technique that allows studying both metallic and non-metallic objects. Although the capture of information with GPR is usually successful, such aspects as the capture settings, the large volume of generated information, and the use and interpretation of such information require high level of skill and experience. This dissertation may be seen as a step forward towards the development of tools able to tackle the problem of lack of knowledge on the WSS buried assets. The main objective of this doctoral work is thus to generate tools and assess their feasibility of application to the characterization of components of WSSs from GPR images. In this work we have carried out laboratory tests specifically designed to propose, develop and evaluate methods for the characterization of the WSS buried components. Additionally, we have conducted field tests, which have enabled us to determine the feasibility of implementing such methodologies under uncontrolled conditions. The methodologies developed are based on techniques of intelligent data analysis. The basic principle of this work has involved the processing of data obtained through the GPR to look for useful information about WSS components, with special emphasis on the pipes. After performing numerous activities, one can conclude that, using GPR images, it is feasible to obtain more information than the typical identification of hyperbolae currently performed. In addition, this information can be observed directly, e.g. more simply, using the methodologies proposed in this doctoral work. These methodologies also prove that it is feasible to identify patterns (especially with the preprocessing algorithm termed Agent race) that provide fairly good approximation of the location of leaks in WSSs. Also, in the case of pipes, one can obtain such other characteristics as diameter and material. The main outcomes of this thesis consist in a series of tools we have developed to locate, identify and visualize WSS components from GPR images. Most interestingly, the data are synthesized and reduced so that the characteristics of the different components of the images recorded in GPR are preserved. The ultimate goal is that the developed tools facilitate decision-making in the technical management of WSSs, and that such tools can even be operated by personnel with limited experience in handling non-destructive methodologies, specifically GPR. / [ES] Con el paso del tiempo, y debido a múltiples actividades operacionales y de mantenimiento, las redes de los sistemas de abastecimiento de agua (SAAs) sufren intervenciones, modificaciones o incluso, son clausuradas, sin que, en muchos casos, estas actividades sean correctamente registradas. El conocimiento de los trazados y características (estado y edad, entre otros) de las tuberías en los SAAs es obviamente necesario para una gestión eficiente y dinámica de tales sistemas. A esta problemática se suma la detección y el control de las fugas de agua. El acceso a información fiable sobre las fugas es una tarea compleja. En muchos casos, las fugas son detectadas cuando los daños en la red son ya considerables, lo que trae consigo altos costes sociales y económicos. En este sentido, los métodos no destructivos (por ejemplo, ground penetrating radar - GPR), pueden ser una respuesta a estas problemáticas, ya que permiten, como se pone de manifiesto en esta tesis, localizar los trazados de las tuberías, identificar características de los componentes y detectar las fugas de agua cuando aún no son significativas. La selección del GPR, en este trabajo se justifica por sus características como técnica no destructiva, que permite estudiar tanto objetos metálicos como no metálicos. Aunque la captura de información con GPR suele ser exitosa, la configuración de la captura, el gran volumen de información, y el uso y la interpretación de la información requieren de alto nivel de habilidad y experiencia por parte del personal. Esta tesis doctoral se plantea como un avance hacia el desarrollo de herramientas que permitan responder a la problemática del desconocimiento de los activos enterrados de los SAAs. El objetivo principal de este trabajo doctoral es, pues, generar herramientas y evaluar la viabilidad de su aplicación en la caracterización de componentes de un SAA, a partir de imágenes GPR. En este trabajo hemos realizado ensayos de laboratorio específicamente diseñados para plantear, elaborar y evaluar metodologías para la caracterización de los componentes enterrados de los SAAs. Adicionalmente, hemos realizado ensayos de campo, que han permitido determinar la viabilidad de aplicación de tales metodologías bajo condiciones no controladas. Las metodologías elaboradas están basadas en técnicas de análisis inteligentes de datos. El principio básico de este trabajo ha consistido en el tratamiento adecuado de los datos obtenidos mediante el GPR, a fin de buscar información de utilidad para los SAAs respecto a sus componentes, con especial énfasis en las tuberías. Tras la realización de múltiples actividades, se puede concluir que es viable obtener más información de las imágenes de GPR que la que actualmente se obtiene con la típica identificación de hipérbolas. Esta información, además, puede ser observada directamente, de manera más sencilla, mediante las metodologías planteadas en este trabajo doctoral. Con estas metodologías se ha probado que también es viable la identificación de patrones (especialmente el pre-procesado con el algoritmo Agent race) que proporcionan aproximación bastante acertada de la localización de las fugas de agua en los SAAs. También, en el caso de las tuberías, se puede obtener otro tipo de características tales como el diámetro y el material. Como resultado de esta tesis se han desarrollado una serie de herramientas que permiten visualizar, identificar y localizar componentes de los SAAs a partir de imágenes de GPR. El resultado más interesante es que los resultados obtenidos son sintetizados y reducidos de manera que preservan las características de los diferentes componentes registrados en las imágenes de GPR. El objetivo último es que las herramientas desarrolladas faciliten la toma de decisiones en la gestión técnica de los SAAs y que tales herramientas puedan ser operadas incluso por personal con una experiencia limitada en el manejo / [CA] Amb el temps, a causa de les múltiples activitats d'operació i manteniment, les xarxes de sistemes d'abastament d'aigua (SAAs) se sotmeten a intervencions, modificacions o fins i tot estan tancades. En molts casos, aquestes activitats no estan degudament registrats. El coneixement dels camins i característiques (estat i edat, etc.) de les canonades d'aigua i sanejament fa evident la necessitat d'una gestió eficient i dinàmica d'aquests sistemes. Aquest problema es veu augmentat en gran mesura tenint en compte la detecció i control de fuites. L'accés a informació fiable sobre les fuites és una tasca complexa. En molts casos, les fugues es detecten quan el dany ja és considerable, el que porta costos socials i econòmics. En aquest sentit, els mètodes no destructius (per exemple, ground penetrating radar - GPR) poden ser una resposta constructiva a aquests problemes, ja que permeten, com s'evidencia en aquesta tesi, per determinar rutes de canonades, identificar les característiques dels components, i detectar les fuites d'aigua quan encara no són significatives. La selecció del GPR en aquest treball es justifica per les seves característiques com a tècnica no destructiva que permet estudiar tant objectes metàl·lics i no metàl·lics. Tot i que la captura d'informació amb GPR sol ser reeixida, aspectes com ara la configuració de captura, el gran volum d'informació que es genera, i l'ús i la interpretació d'aquesta informació requereix alt nivell d'habilitat i experiència. Aquesta tesi pot ser vista com un pas endavant cap al desenvolupament d'eines capaces d'abordar el problema de la manca de coneixement sobre els actius d'aigua i sanejament enterrat. L'objectiu principal d'aquest treball doctoral és, doncs, generar eines i avaluar la seva factibilitat d'aplicació a la caracterització dels components de los SAAs, a partir d'imatges GPR. En aquest treball s'han dut a terme proves de laboratori específicament dissenyats per proposar, desenvolupar i avaluar mètodes per a la caracterització dels components d'aigua i sanejament soterrat. A més, hem dut a terme proves de camp, que ens han permès determinar la viabilitat de la implementació d'aquestes metodologies en condicions no controlades. Les metodologies desenvolupades es basen en tècniques d'anàlisi intel·ligent de dades. El principi bàsic d'aquest treball ha consistit en el tractament de dades obtingudes a través del GPR per buscar informació útil sobre els components d'SAA, amb especial èmfasi en la canonades. Després de realitzar nombroses activitats, es pot concloure que, amb l'ús d'imatges de GPR, és factible obtenir més informació que la identificació típica d'hipèrboles realitzat actualment. A més, aquesta informació pot ser observada directament, per exemple, més simplement, utilitzant les metodologies proposades en aquest treball doctoral. Aquestes metodologies també demostren que és factible per identificar patrons (especialment el pre-processat amb l'algoritme Agent race) que proporcionen bastant bona aproximació de la localització de fuites en SAAs. També, en el cas de tubs, es pot obtenir altres característiques com ara el diàmetre i el material. Els principals resultats d'aquesta tesi consisteixen en una sèrie d'eines que hem desenvolupat per localitzar, identificar i visualitzar els components dels SAAS a partir d'imatges GPR. El resultat més interessant és que els resultats obtinguts són sintetitzats i reduïts de manera que preserven les característiques dels diferents components registrats en les imatges de GPR. L'objectiu final és que les eines desenvolupades faciliten la presa de decisions en la gestió tècnica de SAA, i que tals eines poden fins i tot ser operades per personal amb poca experiència en el maneig de metodologies no destructives, específicament GPR. / Ayala Cabrera, D. (2015). Characterization of components of water supply systems from GPR images and tools of intelligent data analysis [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/59235 / TESIS / Premios Extraordinarios de tesis doctorales

Recent progress in fundamental biological sciences and medicine has considerably increased the quantity ofdata that can be studied and processed. The main limitation now is not retrieving data, but rather extractinguseful biological insights from the large datasets accumulated. More recent advances have provided detailedhigh-density data regarding metabolism (metabolomics) and protein expression (proteomics). Clearly, no single analytic methods, can provide a comprehensive understanding. Rather, the ability to link available datatogether in a coherent manner is required to obtain a complete view. The improving application of MachineLearning (ML) techniques provides the means to make continuous progress in processing complex data sets.A brief discussion is offered on the advantages of ML, the state-of-the-art in Deep Learning (DL) for proteinpredictions and the importance of ML in biological data processing. Noise stemming from incorrect classification or arbitrary/ambiguous labelling of data may arise when ML techniques are applied to large datasets. Furthermore, the stochasticity of biological systems needs to be considered for correctly evaluating theoutputs. Here we show the potential of a workflow to respond biological questions taking into consideration aperturbation of the biological data.  For controlling the applicability of models and maximizing the predictivity, in silico filtering schemescan usefully be applied as an “Ockham’s razor” before using any ML technique. After reviewing differentDL approaches for protein prediction purposes, this work shows that a computational approach in filteringsteps is a valuable tool for proteins classification when biological features are not fully annotated or reviewed.The in silico approach has identified putative proline transporters in fungi and plants as well as carotenoidbiosynthetic gene products in the plant family Brassicaceae. The proposed method is suitable for extractingfeatures of classification and then maximizing the use of a DL approach.

No description available.

Although high-level synthesis has been researched for many years, synthesizing minimum hardware implementations under a throughput constraint for computationally intensive algorithms remains a challenge. In this thesis, three important techniques are studied carefully and applied in an integrated way to meet this challenging synthesis requirement. The first is pipeline scheduling, which generates a pipelined schedule that meets the throughput requirement. The second is module selection, which decides the most appropriate circuit module for each operation. The third is resource sharing, which reuses a circuit module by sharing it between multiple operations. This work shows that combining module selection and resource sharing while performing pipeline scheduling can significantly reduce the hardware area, by either using slower, more area-efficient circuit modules or by time-multiplexing faster, larger circuit modules, while meeting the throughput constraint. The results of this work show that the combined approach can generate on average 43% smaller hardware than possible when a single technique (resource sharing or module selection) is applied. There are four major contributions of this work. First, given a fixed throughput constraint, it explores all feasible frequency and data introduction interval design points that meet this throughput constraint. This enlarged pipelining design space exploration results in superior hardware architectures than previous pipeline synthesis work because of the larger sapce. Second, the module selection algorithm in this work considers different module architectures, as well as different pipelining options for each architecture. This not only addresses the unique architecture of most FPGA circuit modules, it also performs retiming at the high-level synthesis level. Third, this work proposes a novel approach that integrates the three inter-related synthesis techniques of pipeline scheduling, module selection and resource sharing. To the author's best knowledge, this is the first attempt to do this. The integrated approach is able to identify more efficient hardware implementations than when only one or two of the three techniques are applied. Fourth, this work proposes and implements several algorithms that explore the combined pipeline scheduling, module selection and resource sharing design space, and identifies the most efficient hardware architecture under the synthesis constraint. These algorithms explore the combined design space in different ways which represents the trade off between algorithm execution time and the size of the explored design space.