Thesis (M.S.)--West Virginia University, 2005. / Title from document title page. Document formatted into pages; contains xi, 79 p. : ill. Includes abstract. Includes bibliographical references (p. 67-70).

Thesis (M.S.)--West Virginia University, 2000. / Title from document title page. Document formatted into pages; contains xii, 119 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 106-107).

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1992. / Vita. Abstract. Includes bibliographical references (leaves 81-83). Also available via the Internet.

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1993. / Vita. Abstract. Includes bibliographical references (leaves 53-56). Also available via the Internet.

Made available in DSpace on 2015-03-03T11:52:40Z (GMT). No. of bitstreams: 0 Previous issue date: 2014-06-13Bitstream added on 2015-03-03T12:06:10Z : No. of bitstreams: 1 000801083.pdf: 1280442 bytes, checksum: 6dcfc6fb20131fddca0a32bff15754cf (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Nestre trabalho é desenvolvida uma modelagem matemática para os ciclos irreversíveis Otto e Diesel. Os ciclos são analisados entre dois reservatórios com taxa de capacidade térmica infinita, com os processos de troca de calor ocorrendo em trocadores de calor entre o fluido de trabalho e os reservatórios térmicos. As irreversibilidades são decorrentes dos processos de troca de calor ocorrendo em tempo finito, da taxa de perda de calor do reservatório de alta temperatura para o reservatório de baixa temperatura e dos processos de compressão e expansão não-isoentrópicas. São utilizados três critérios de otimização: função ecológica, coeficiente ecológico de desempenho e potência máxima de saída. Estas funções são otimizadas com relação à temperatura de entrada no processo de adição de calor. São analisados as otimizações ecológicas e então comparadas com a potência máxima. Os resultados são apresentados através das curvas de potência e critério ecológico, eficiência térmica ecológico e taxa de geração de entropia e critério ecológico. São analisados os comportamentos de potência líquida, eficiência térmica e taxa de geração de entropia otimizadas ecologicamente através dos quais são avaliadas as influências de alguns parâmetros nos seus comportamentos. Por fim, são analisadas as razões entre a potência otimizada por critérios ecológicos e a potência máxima, eficiência térmica otimizada por critérios ecológicos e a eficiência térmica na condição de potência máxima, a taxa de geração de entropia otimizada por critérios ecológicos e a taxa de geração de entropia na condição de potência máxima. A análise dos resultados comprova que as otimizações ecológicas apresentam o melhor compromisso entre potência líquida e o ambiente. Os resultados poderão ser utilizados como critério relevante no aperfeiçoamento de projetos dos motores de combustão interna / In this work is developed a mathematical model for the irreversible Otto and Diesel cycles. The cycle is analyzed between two reservois with infinite thermal capacitance, where the processes of heat exchange occuring in the heat exchangers between the working fluid and the thermal reservoir at constant temperatures. The irreversibilities follow from the heat exchange processes occurring in finite time, the loss of heat from the hot source to the cold source and the noisentropic compression and expansion processes. Three optimization criteria are used: ecological function, ecological coefficient of performance and maximum power output. These functions are optimized with respect to the inlet temperature of heat addition process. Ecological optimizations are analyzed and compared to maximum power. The results are presented through the power and ecological creteria, thermal efficiency and ecological criteria and entropy generation rate and ecological criteria curves. The results are presented though the power curves and ecological criteria, thermal efficiency and ecological and entropy generation rate and ecological criteria. Analyzes the behavior of power, efficiency and rate of entropy generation ecologically optimized through which they are evaluated the influences of some parameters on their behavior. Finally, we analyze the ratio between ecological criteria for optimum power and maximum power, optimized thermal efficiency by ecological criteria and the maximum power efficiency, the ratio between the entropy generation rate optimized for ecological criteria and entropy generation rate of maximum power. The results show that the ecological optimizations present the best compromisse between power and environment. The results can be used as an important criterion in developing projects of internal combustion engines

Submitted by Santos Davilene (davilenes@ufba.br) on 2016-05-30T15:55:34Z No. of bitstreams: 1 Dissertação_Mestrado_Clicia(1).pdf: 2228201 bytes, checksum: d990a114eac5a988c57ba6d1e22e8f99 (MD5) / Made available in DSpace on 2016-05-30T15:55:34Z (GMT). No. of bitstreams: 1 Dissertação_Mestrado_Clicia(1).pdf: 2228201 bytes, checksum: d990a114eac5a988c57ba6d1e22e8f99 (MD5) / Transformar os dados armazenados em informações úteis tem sido um desafio cada vez maior e mais complexo a medida em que o volume de dados produzidos todos os dias aumenta. Nos últimos anos, conceitos e tecnologias de Big Data têm sido amplamente utilizados como solução para o gerenciamento de grandes quantidades de dados em diferentes domínios. A proposta deste trabalho diz respeito `a utiliza¸c˜ao de técnicas de ETL (extração,transformação e carga) no desenvolvimento de um módulo de pré-processamento para o pareamento probabilístico de registros em bases de dados na área de Saúde Pública. A utiliza¸c˜ao da ferramenta de processamento distribuído do Spark garante o tratamento adequado para o contexto de Big Data em que esta pesquisa está inserida, gerando respostas em tempo hábil.

In this thesis Direct Numerical Simulation (DNS) is used to investigate the development of turbulent premixed flame kernels during the early stages of growth typical of the period following spark ignition. Two distinct aspects of this phase are considered: the interaction of the expanding kernel with a field of decaying turbulence, and the chemical and thermo-diffusive response of the flame for different fresh-gas compositions. In the first part of the study, three-dimensional, repeated simulations with single-step chemistry are used to generate ensemble statistics of global flame growth. The surface-conditioned mean fluid-velocity magnitude is found to vary significantly across different isosurfaces of the reaction progress variable, and this is shown to lead to a bias in the distribution of the Surface Density Function (SDF) around the developing flame. Two-dimensional simulations in an extended domain indicate that this effect translates into a similar directional bias in the Flame Surface Density (FSD) at later stages in the kernel development. Properties of the fresh gas turbulence decay are assessed from an independent, non-reacting simulation database. In the second part of this study, two-dimensional simulations with a detailed 68-step reaction mechanism are used to investigate the thermo-diffusive response of pure methane-air, and hydrogen-enriched methane-air flames. The changes in local and global behaviour due to the different laminar flame characteristics, and the response of the flames to strain and curvature are examined at different equivalence ratios and turbulence intensities. Mechanisms leading to flame quenching are discussed and the effect of mean flame curvature is assessed through comparison with an equivalent planar flame. The effects of hydrogen addition are found to be particularly pronounced in flame kernels due to the higher positive stretch rates and reduced thermo-diffusive stability of hydrogen-enriched flames.

Four silicon nitride powder blends vary in starting powder characteristics, glass chemistry, and phase composition. This work focuses on how these properties influence densification behavior, microstructural development, and the resulting mechanical performance of dense ceramics. Previous work completed on alpha-rich, low oxide containing (8 wt%), and fine silicon nitride powder (GS-44) showed high hardness equiaxed with grained ceramic. GS-44 served as an excellent precursor for the matrix phase material in graphene reinforced composites, which resulted in 235% increase in toughness and high hardness retention [1] with the addition of 1.5 vol% graphene. As the GS-44 powder is no longer in production, investigative work into other commercial powders and customization of powder blends was initiated. Commercial blends were selected based on availability, high alpha content, fine particle size, and additive chemistry (Al2O3, MgO, and Y2O3). The objective was to understand which powder characteristics led to a ceramic design that contained high hardness, strength, and toughness properties in order to increase the use of silicon nitride in extreme temperature environments. One such example is aerospace and structural applications that require a high-performance material that is lightweight and good thermal stability. Strong covalent bonding in silicon nitride make densification of powders extremely difficult; thereby, sintering additives are necessary to promote liquid phase sintering processes. Compaction of ceramic powders was carried out using a spark plasma sintering (SPS) furnace by utilizing a pulsed direct current through a conductive graphite die that encapsulates the sample powder. SPS was preferred over other conventional sintering methods owing to its high heating rate and short dwell times at the sintering target temperature. Thus, SPS provides superior control for tailoring the final silicon nitride properties by producing a hard alpha-phase and tough beta-phase microstructures. The custom blend developed had an appreciable amount of media wear included during the milling process that increased the additive content. Development of the custom blend was used to understand the effect of a larger additive content. Commercial GS-44 blend was used as the control to track the effect of adjusting specific surface area and oxide content in silicon nitride powder systems (HCS-M, C-R3, and UA-SN). The mechanical results for the four matrix systems, showed that toughness increased with grain coarsening and minimization of alumina content in beta silicon nitride. Based on these findings it is important to determine tradeoffs (i.e. balance of high hardness, toughness, and strength) to engineer an optimal ceramic that can be used for structural and aerospace applications.

Data cleansing approaches have usually focused on detecting and fixing errors with little attention to big data scaling. This presents a serious impediment since identify- ing and repairing dirty data often involves processing huge input datasets, handling sophisticated error discovery approaches and managing huge arbitrary errors. With large datasets, error detection becomes overly expensive and complicated especially when considering user-defined functions. Furthermore, a distinctive algorithm is de- sired to optimize inequality joins in sophisticated error discovery rather than na ̈ıvely parallelizing them. Also, when repairing large errors, their skewed distribution may obstruct effective error repairs. In this dissertation, I present solutions to overcome the above three problems in scaling data cleansing. First, I present BigDansing as a general system to tackle efficiency, scalability, and ease-of-use issues in data cleansing for Big Data. It automatically parallelizes the user’s code on top of general-purpose distributed platforms. Its programming inter- face allows users to express data quality rules independently from the requirements of parallel and distributed environments. Without sacrificing their quality, BigDans- ing also enables parallel execution of serial repair algorithms by exploiting the graph representation of discovered errors. The experimental results show that BigDansing outperforms existing baselines up to more than two orders of magnitude. Although BigDansing scales cleansing jobs, it still lacks the ability to handle sophisticated error discovery requiring inequality joins. Therefore, I developed IEJoin as an algorithm for fast inequality joins. It is based on sorted arrays and space efficient bit-arrays to reduce the problem’s search space. By comparing IEJoin against well- known optimizations, I show that it is more scalable, and several orders of magnitude faster. BigDansing depends on vertex-centric graph systems, i.e., Pregel, to efficiently store and process discovered errors. Although Pregel scales general-purpose graph computations, it is not able to handle skewed workloads efficiently. Therefore, I introduce Mizan, a Pregel system that balances the workload transparently during runtime to adapt for changes in computing needs. Mizan is general; it does not assume any a priori knowledge of the graph structure or the algorithm behavior. Through extensive evaluations, I show that Mizan provides up to 84% improvement over techniques leveraging static graph pre-partitioning.

Current stoichiometric spark-ignited engine technologies require costly catalytic converters for reductions in tailpipe emissions. Load control is achieved by using a throttle, which is a leading contributor to reductions in efficiency. Spark-ignited lean burn natural gas engines have been proven to be more efficient and emit fewer pollutants than their stoichiometric counterparts. Load reduction in these engines can be achieved by regulating the air/fuel ratio of the intake charge thereby reducing the efficiency penalties inherent to throttling. Partially stratified charge (PSC) can provide further reductions in emissions and improvements in efficiency by extending the lean limit of operation. PSC is achieved by the ignition of a small quantity of natural gas in the vicinity of the spark plug. This creates an easily ignitable mixture at the spark plug electrodes, thereby providing a high energy ignition source for the ultra-lean bulk charge. Stratified charge engine operation using direct injection (DI) has been proposed as a method of bridging the throttleless load reduction gap between idle and ultra-lean conditions. A previous study was conducted to determine if PSC can provide a high-energy ignition source in a direct injected stratified charge engine. Difficulties with igniting the PSC injections in an air-only bulk charge were encountered. This study focuses on a fundamental Schlieren image-based analysis of PSC combustion. Natural gas was injected through a modified spark plug located in an optically accessible combustion bomb. The relationships between PSC injection timing, fuel supply pressure and spark timing were investigated. Spark timing is defined as the duration between commanded start of injection and the time of spark. As the fuel supply pressure was increased, the minimum spark timing that lead to successful combustion also increased. The largest spark timing window that led to successful combustion was determined to be 80 ms wide at an injection fuel supply pressure of 300 psi. The amount of unburned natural gas increased with increasing spark timing. A cold flow study of the PSC injection system was also conducted. The PSC injection solenoid was found to have a consistent average injection delay of 1.95 ms. The slope of the linear response region of observed injection duration to commanded injection duration was 8.4. Due to plenum effects, the average observed injection duration of the entire PSC system was an order of magnitude longer than the commanded injection duration and was found to vary significantly with fuel supply pressure. / Applied Science, Faculty of / Mechanical Engineering, Department of / Graduate