447 resultados para SPARK


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The available literature has been surveyed to determine the parameters affecting fuelling requirements of spark ignition engines and their relation to engine performance and emissions. Theories and experiment relating to two phase and multi-component flows have also been examined and the techniques employed in the measurement of droplet sizes and liquid wall films have been reviewed. Following preliminary steady flow visualisation experiments to examine the trajectories of droplets discharging from the valve port an extensive practical investigation of the spectrum of droplet sizes formed by the break up of the wall film has produced results which have been correlated in terms of the important fuel and airflow parameters. It is concluded that the Sauter mean diameter of droplets formed by the break up of the wall film will vary between 70 and 150 m, depending on the operating conditions of the engine. The spectra of droplet sizes measured show that a significant proportion of the total mass of the wall film breaks into drops which will be too large to burn completely and, by comparison with measurements of unburned hydrocarbon emissions from engines supplied with a homogeneous mixture of air and gaseous hydrocarbons, it is concluded that the droplets from the wall film are likely to increase emissions by 50%.

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Electrical and thermal transport properties of the carbon nanotube bulk material compacted by spark plasma sintering have been investigated. The electrical conductivity of the as-prepared sample shows a lnT dependence from 4 to 50 K, after which the conductivity begins to increase approximately linearly with temperature. A magnetic field applied perpendicularly to the sample increases the electrical conductivity in the range of 0-8T at all testing temperatures, indicating that the sample possesses the two-dimensional weak localization at lower temperatures (?50 K), while behaviors like a semimetal at higher temperatures (?50 K). This material acts like a uniform compact consisting of randomly distributed two dimensional graphene layers. For the same material, the thermal conductivity is found to decrease almost linearly with decreasing temperature, similar to that of a single multi-walled carbon nanotube. Magnetic fields applied perpendicularly to the sample cause the thermal conductivity to decrease significantly, but the influence of the magnetic fields becomes weak when temperature increases.

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The surfaces of bulk carbon nanotubes compacted by plasma spark sintering have been modified with polytetrofluorethylene, thereby producing a super-hydrophobic surface with a contact angle above 160°. The surface roughness and air trapped in pores and between the polytetrofluorethylene particles are responsible for the super-hydrophobility. The material can be machined into desired shapes with fine and complex channels, allowing internal surfaces to also be super-hydrophobic.

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In this paper we evaluate and compare two representativeand popular distributed processing engines for large scalebig data analytics, Spark and graph based engine GraphLab. Wedesign a benchmark suite including representative algorithmsand datasets to compare the performances of the computingengines, from performance aspects of running time, memory andCPU usage, network and I/O overhead. The benchmark suite istested on both local computer cluster and virtual machines oncloud. By varying the number of computers and memory weexamine the scalability of the computing engines with increasingcomputing resources (such as CPU and memory). We also runcross-evaluation of generic and graph based analytic algorithmsover graph processing and generic platforms to identify thepotential performance degradation if only one processing engineis available. It is observed that both computing engines showgood scalability with increase of computing resources. WhileGraphLab largely outperforms Spark for graph algorithms, ithas close running time performance as Spark for non-graphalgorithms. Additionally the running time with Spark for graphalgorithms over cloud virtual machines is observed to increaseby almost 100% compared to over local computer clusters.

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© IMechE 2014. Controlled auto-ignition, also known as homogeneous charge compression ignition, has been the subject of extensive research because of their ability to provide simultaneous reductions in fuel consumption and NOx emissions from a gasoline engine. However, due to its limited operation range, switching between controlled auto-ignition and spark ignition combustion is needed to cover the complete operating range of a gasoline engine for passenger car applications. Previous research has shown that the spark ignition -controlled auto-ignition hybrid combustion (SCHC) has the potential to control the ignition timing and heat release process during the mode transition operations. However, it was found that the SCHC is often characterized with large cycle-to-cycle variations. The cyclic variations in the in-cylinder pressure are particularly noticeable in terms of both their peak values and timings while the coefficient of variation in the indicated mean effective pressure is much less. In this work, the cyclic variations in SCHC operations were analyzed by means of in-cylinder pressure and heat release analysis in a single-cylinder gasoline engine equipped with Variable Valve Actuation (VVA) systems. First, characteristics of the in-cylinder pressure traces during the spark ignition-controlled auto-ignition hybrid combustion operation are presented and their heat release processes analyzed. In order to clarify the contribution to heat release and cyclic variation in SCHC, a new method is introduced to identify the occurrence of auto-ignition combustion and its subsequent heat release process. Based on the new method developed, the characteristics of cyclic variations in the maximum rate of pressure rise and different stages of heat release process have been analyzed and discussed.

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Technologies for Big Data and Data Science are receiving increasing research interest nowadays. This paper introduces the prototyping architecture of a tool aimed to solve Big Data Optimization problems. Our tool combines the jMetal framework for multi-objective optimization with Apache Spark, a technology that is gaining momentum. In particular, we make use of the streaming facilities of Spark to feed an optimization problem with data from different sources. We demonstrate the use of our tool by solving a dynamic bi-objective instance of the Traveling Salesman Problem (TSP) based on near real-time traffic data from New York City, which is updated several times per minute. Our experiment shows that both jMetal and Spark can be integrated providing a software platform to deal with dynamic multi-optimization problems.

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The present paper reports synthesis of novel AlFeCuCrMgx (x = 0, 0.5, 1, 1.7 mol) high entropy alloys (HEAs) by mechanical alloying (MA) followed by spark plasma sintering (SPS). Phase evolution, microstructure and phase transformation study of the sintered alloy were investigated by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and differential scanning calorimetry (DSC). XRD of the sintered alloys revealed the formation of two BCC phases in the AlFeCuCr alloy and more complex structures in AlFeCuCrMgx (x = 0.5, 1, 1.7) alloys containing AlFe type, BCC, and Cu2Mg type phases. TEM bright field image and selected area diffraction pattern (SAED) revealed the formation of tetragonal closed packed Cr precipitates within the Cu2Mg phase of AlFeCuCrMgx alloys (x = 0.5, 1, 1.7). DSC study of the alloys revealed no substantial phase change up to 1000 °C for AlFeCuCr alloy. Although, for x = 0.5, 1 & 1.7 phase transformation occurs at 818 °C, 885 °C & 483 °C respectively. Mg content had a significant effect on hardness, increasing to a peak hardness of 853 HVN for AlFeCuCrMg0.5 alloy before decreasing to 533 HVN for the AlFeCuCrMg1.7 alloy. The phase evolution in these alloys has been considered using thermodynamic parameters, and the structure-property relationship has also been proposed by conventional strengthening mechanisms.

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Hypersonic aerospace vehicles are severely limited by the lack of adequate high temperature materials that can withstand the harsh hypersonic environment. Tantalum carbide (TaC), with a melting point of 3880°C, is an ultrahigh temperature ceramic (UHTC) with potential applications such as scramjet engines, leading edges, and zero erosion nozzles. However, consolidation of TaC to a dense structure and its low fracture toughness are major challenges that make it currently unviable for hypersonic applications. In this study, Graphene NanoPlatelets (GNP) reinforced TaC composites are synthesized by spark plasma sintering (SPS) at extreme conditions of 1850˚C and 80-100 MPa. The addition of GNP improves densification and enhances fracture toughness of TaC by up to ~100% through mechanisms such as GNP bending, sliding, pull-out, grain wrapping, crack bridging, and crack deflection. Also, TaC-GNP composites display improved oxidation behavior over TaC when exposed to a high temperature plasma flow exceeding 2500 ˚C.

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With the emergence of the big data age, the issue of how to obtain valuable knowledge from a dataset efficiently and accurately has attracted increasingly attention from both academia and industry. This paper presents a Parallel Random Forest (PRF) algorithm for big data on the Apache Spark platform. The PRF algorithm is optimized based on a hybrid approach combining data-parallel and task-parallel optimization. From the perspective of data-parallel optimization, a vertical data-partitioning method is performed to reduce the data communication cost effectively, and a data-multiplexing method is performed is performed to allow the training dataset to be reused and diminish the volume of data. From the perspective of task-parallel optimization, a dual parallel approach is carried out in the training process of RF, and a task Directed Acyclic Graph (DAG) is created according to the parallel training process of PRF and the dependence of the Resilient Distributed Datasets (RDD) objects. Then, different task schedulers are invoked for the tasks in the DAG. Moreover, to improve the algorithm's accuracy for large, high-dimensional, and noisy data, we perform a dimension-reduction approach in the training process and a weighted voting approach in the prediction process prior to parallelization. Extensive experimental results indicate the superiority and notable advantages of the PRF algorithm over the relevant algorithms implemented by Spark MLlib and other studies in terms of the classification accuracy, performance, and scalability.

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This paper discusses the ongoing design and use of a digital community noticeboard situated in a suburban hub. The design intention is to engage residents, collect and display local information and communications, and spark discussion. A key contribution is an understanding of Situated Display navigation that aids retrieval from a long-term collection created by and for suburban community, and engaging qualities of this collection.

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The degradation of high voltage electrical insulation is a prime factor that can significantly influence the reliability performance and the costs of maintaining high voltage electricity networks. Little information is known about the system of localized degradation from corona discharges on the relatively new silicone rubber sheathed composite insulators that are now being widely used in high voltage applications. This current work focuses on the fundamental principles of electrical corona discharge phenomena to provide further insights to where damaging surface discharges may localize and examines how these discharges may degrade the silicone rubber material. Although water drop corona has been identified by many authors as a major cause of deterioration of silicone rubber high voltage insulation until now no thorough studies have been made of this phenomenon. Results from systematic measurements taken using modern digital instrumentation to simultaneously record the discharge current pulses and visible images associated with corona discharges from between metal electrodes, metal electrodes and water drops, and between waters drops on the surface of silicone rubber insulation, using a range of 50 Hz voltages are inter compared. Visual images of wet electrodes show how water drops can play a part in encouraging flashover, and the first reproducible visual images of water drop corona at the triple junction of water air and silicone rubber insulation are presented. A study of the atomic emission spectra of the corona produced by the discharge from its onset up to and including spark-over, using a high resolution digital spectrometer with a fiber optic probe, provides further understanding of the roles of the active species of atoms and molecules produced by the discharge that may be responsible for not only for chemical changes of insulator surfaces, but may also contribute to the degradation of the metal fittings that support the high voltage insulators. Examples of real insulators and further work specific to the electrical power industry are discussed. A new design concept to prevent/reduce the damaging effects of water drop corona is also presented.

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For most of the 20th Century a ‘closed’ system of adoption was practised throughout Australia and other modern Western societies. This ‘closed’ system was characterised by sealed records; amended birth certificates to conceal the adoption, and prohibited contact with all biological family. Despite claims that these measures protected these children from the taint of illegitimacy the central motivations were far more complex, involving a desire to protect couples from the stigma of infertility and to provide a socially acceptable family structure (Triseliotis, Feast, & Kyle, 2005; Marshall & McDonald, 2001). From the 1960s significant evidence began to emerge that many adopted children and adults were experiencing higher incidences of psychological difficulties, characterised by problems with psychological adjustment, building self-esteem and forming a secure personal identity. These difficulties became grouped under the term ‘genealogical bewilderment’. As a result, new policies and practices were introduced to try to place the best interests of the child at the forefront. These changes reflected new understandings of adoption; as not only an individual process but also as a social and relational process that continues throughout life. Secrecy and the withholding of birth information are now prohibited in the overwhelming majority of all domestic adoptions processed in Australia (Marshall & McDonald, 2001). One little known consequence of this ‘closed’ system of adoption was the significant number of children who were never told of their adoptive status. As a consequence, some have discovered or had this information disclosed to them, as adults. The first study that looked at the late discovery of genetic origins experiences was conducted by the Post Adoption Resource Centre in New South Wales in 1999. This report found that the participants in their study expressed feelings of disbelief, confusion, anger, sorrow and loss. Further, the majority of participants continued to struggle with issues arising from this intentional concealment of their genetic origins (Perl & Markham, 1999). A second and more recent study (Passmore, Feeney & Foulstone, 2007) looked at the issue of secrecy in adoptive families as part of a broader study of 144 adult adoptees. This study found that secrecy and/or lies or misinformation on the part of adoptive parents had negative effects on both personal identity and relationships with others. The authors noted that those adoptees who found out about their adoption as adults were ‘especially likely to feel a sense of betrayal’ (p.4). Over recent years, stories of secrecy and late discovery have also started to emerge from sperm donor conceived adults (Spencer, 2007; Turner & Coyle, 2000). Current research evidence shows that although a majority of couples during the donor assisted conception process indicate that they intend to tell the offspring about their origins, as many as two-thirds or more of couples continue to withhold this information from their children (Akker, 2006; Gottlieb, A. McWhinnie, 2001; Salter-Ling, Hunter, & Glover, 2001). Why do they keep this secret? Infertility involves a range of complex factors that are often left unresolved or poorly understood by those choosing insemination by donor as a form of family building (Schaffer, J. A., & Diamond, R., 1993). These factors may only impact after the child is born, when resemblance talk becomes most pronounced. Resemblance talk is an accepted form of public discourse and a social convention that legitimises the child as part of the family and is part of the process of constructing the child’s identity within the family. Couples tend to become focused on resemblance as this is where they feel most vulnerable, and the lack of resemblance to the parenting father may trigger his sense of loss (Becker, Butler, & Nachtigall, 2005).

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Electrostatic discharge is the sudden and brief electric current that flashes between two objects at different voltages. This is a serious issue ranging in application from solid-state electronics to spectacular and dangerous lightning strikes (arc flashes). The research herein presents work on the experimental simulation and measurement of the energy in an electrostatic discharge. The energy released in these discharges has been linked to ignitions and burning in a number of documented disasters and can be enormously hazardous in many other industrial scenarios. Simulations of electrostatic discharges were designed to specifications by IEC standards. This is typically based on the residual voltage/charge on the discharge capacitor, whereas this research examines the voltage and current in the actual spark in order to obtain a more precise comparative measurement of the energy dissipated.