926 resultados para Fluid mechanics - Data processing


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This paper is part of a special issue of Applied Geochemistry focusing on reliable applications of compositional multivariate statistical methods. This study outlines the application of compositional data analysis (CoDa) to calibration of geochemical data and multivariate statistical modelling of geochemistry and grain-size data from a set of Holocene sedimentary cores from the Ganges-Brahmaputra (G-B) delta. Over the last two decades, understanding near-continuous records of sedimentary sequences has required the use of core-scanning X-ray fluorescence (XRF) spectrometry, for both terrestrial and marine sedimentary sequences. Initial XRF data are generally unusable in ‘raw-format’, requiring data processing in order to remove instrument bias, as well as informed sequence interpretation. The applicability of these conventional calibration equations to core-scanning XRF data are further limited by the constraints posed by unknown measurement geometry and specimen homogeneity, as well as matrix effects. Log-ratio based calibration schemes have been developed and applied to clastic sedimentary sequences focusing mainly on energy dispersive-XRF (ED-XRF) core-scanning. This study has applied high resolution core-scanning XRF to Holocene sedimentary sequences from the tidal-dominated Indian Sundarbans, (Ganges-Brahmaputra delta plain). The Log-Ratio Calibration Equation (LRCE) was applied to a sub-set of core-scan and conventional ED-XRF data to quantify elemental composition. This provides a robust calibration scheme using reduced major axis regression of log-ratio transformed geochemical data. Through partial least squares (PLS) modelling of geochemical and grain-size data, it is possible to derive robust proxy information for the Sundarbans depositional environment. The application of these techniques to Holocene sedimentary data offers an improved methodological framework for unravelling Holocene sedimentation patterns.

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Thesis (Ph.D.)--University of Washington, 2016-08

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Recent advances in the massively parallel computational abilities of graphical processing units (GPUs) have increased their use for general purpose computation, as companies look to take advantage of big data processing techniques. This has given rise to the potential for malicious software targeting GPUs, which is of interest to forensic investigators examining the operation of software. The ability to carry out reverse-engineering of software is of great importance within the security and forensics elds, particularly when investigating malicious software or carrying out forensic analysis following a successful security breach. Due to the complexity of the Nvidia CUDA (Compute Uni ed Device Architecture) framework, it is not clear how best to approach the reverse engineering of a piece of CUDA software. We carry out a review of the di erent binary output formats which may be encountered from the CUDA compiler, and their implications on reverse engineering. We then demonstrate the process of carrying out disassembly of an example CUDA application, to establish the various techniques available to forensic investigators carrying out black-box disassembly and reverse engineering of CUDA binaries. We show that the Nvidia compiler, using default settings, leaks useful information. Finally, we demonstrate techniques to better protect intellectual property in CUDA algorithm implementations from reverse engineering.

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The role of computer modeling has grown recently to integrate itself as an inseparable tool to experimental studies for the optimization of automotive engines and the development of future fuels. Traditionally, computer models rely on simplified global reaction steps to simulate the combustion and pollutant formation inside the internal combustion engine. With the current interest in advanced combustion modes and injection strategies, this approach depends on arbitrary adjustment of model parameters that could reduce credibility of the predictions. The purpose of this study is to enhance the combustion model of KIVA, a computational fluid dynamics code, by coupling its fluid mechanics solution with detailed kinetic reactions solved by the chemistry solver, CHEMKIN. As a result, an engine-friendly reaction mechanism for n-heptane was selected to simulate diesel oxidation. Each cell in the computational domain is considered as a perfectly-stirred reactor which undergoes adiabatic constant- volume combustion. The model was applied to an ideally-prepared homogeneous- charge compression-ignition combustion (HCCI) and direct injection (DI) diesel combustion. Ignition and combustion results show that the code successfully simulates the premixed HCCI scenario when compared to traditional combustion models. Direct injection cases, on the other hand, do not offer a reliable prediction mainly due to the lack of turbulent-mixing model, inherent in the perfectly-stirred reactor formulation. In addition, the model is sensitive to intake conditions and experimental uncertainties which require implementation of enhanced predictive tools. It is recommended that future improvements consider turbulent-mixing effects as well as optimization techniques to accurately simulate actual in-cylinder process with reduced computational cost. Furthermore, the model requires the extension of existing fuel oxidation mechanisms to include pollutant formation kinetics for emission control studies.

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The only method used to date to measure dissolved nitrate concentration (NITRATE) with sensors mounted on profiling floats is based on the absorption of light at ultraviolet wavelengths by nitrate ion (Johnson and Coletti, 2002; Johnson et al., 2010; 2013; D’Ortenzio et al., 2012). Nitrate has a modest UV absorption band with a peak near 210 nm, which overlaps with the stronger absorption band of bromide, which has a peak near 200 nm. In addition, there is a much weaker absorption due to dissolved organic matter and light scattering by particles (Ogura and Hanya, 1966). The UV spectrum thus consists of three components, bromide, nitrate and a background due to organics and particles. The background also includes thermal effects on the instrument and slow drift. All of these latter effects (organics, particles, thermal effects and drift) tend to be smooth spectra that combine to form an absorption spectrum that is linear in wavelength over relatively short wavelength spans. If the light absorption spectrum is measured in the wavelength range around 217 to 240 nm (the exact range is a bit of a decision by the operator), then the nitrate concentration can be determined. Two different instruments based on the same optical principles are in use for this purpose. The In Situ Ultraviolet Spectrophotometer (ISUS) built at MBARI or at Satlantic has been mounted inside the pressure hull of a Teledyne/Webb Research APEX and NKE Provor profiling floats and the optics penetrate through the upper end cap into the water. The Satlantic Submersible Ultraviolet Nitrate Analyzer (SUNA) is placed on the outside of APEX, Provor, and Navis profiling floats in its own pressure housing and is connected to the float through an underwater cable that provides power and communications. Power, communications between the float controller and the sensor, and data processing requirements are essentially the same for both ISUS and SUNA. There are several possible algorithms that can be used for the deconvolution of nitrate concentration from the observed UV absorption spectrum (Johnson and Coletti, 2002; Arai et al., 2008; Sakamoto et al., 2009; Zielinski et al., 2011). In addition, the default algorithm that is available in Satlantic sensors is a proprietary approach, but this is not generally used on profiling floats. There are some tradeoffs in every approach. To date almost all nitrate sensors on profiling floats have used the Temperature Compensated Salinity Subtracted (TCSS) algorithm developed by Sakamoto et al. (2009), and this document focuses on that method. It is likely that there will be further algorithm development and it is necessary that the data systems clearly identify the algorithm that is used. It is also desirable that the data system allow for recalculation of prior data sets using new algorithms. To accomplish this, the float must report not just the computed nitrate, but the observed light intensity. Then, the rule to obtain only one NITRATE parameter is, if the spectrum is present then, the NITRATE should be recalculated from the spectrum while the computation of nitrate concentration can also generate useful diagnostics of data quality.

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The CATARINA Leg1 cruise was carried out from June 22 to July 24 2012 on board the B/O Sarmiento de Gamboa, under the scientific supervision of Aida Rios (CSIC-IIM). It included the occurrence of the OVIDE hydrological section that was performed in June 2002, 2004, 2006, 2008 and 2010, as part of the CLIVAR program (name A25) ), and under the supervision of Herlé Mercier (CNRSLPO). This section begins near Lisbon (Portugal), runs through the West European Basin and the Iceland Basin, crosses the Reykjanes Ridge (300 miles north of Charlie-Gibbs Fracture Zone, and ends at Cape Hoppe (southeast tip of Greenland). The objective of this repeated hydrological section is to monitor the variability of water mass properties and main current transports in the basin, complementing the international observation array relevant for climate studies. In addition, the Labrador Sea was partly sampled (stations 101-108) between Greenland and Newfoundland, but heavy weather conditions prevented the achievement of the section south of 53°40’N. The quality of CTD data is essential to reach the first objective of the CATARINA project, i.e. to quantify the Meridional Overturning Circulation and water mass ventilation changes and their effect on the changes in the anthropogenic carbon ocean uptake and storage capacity. The CATARINA project was mainly funded by the Spanish Ministry of Sciences and Innovation and co-funded by the Fondo Europeo de Desarrollo Regional. The hydrological OVIDE section includes 95 surface-bottom stations from coast to coast, collecting profiles of temperature, salinity, oxygen and currents, spaced by 2 to 25 Nm depending on the steepness of the topography. The position of the stations closely follows that of OVIDE 2002. In addition, 8 stations were carried out in the Labrador Sea. From the 24 bottles closed at various depth at each stations, samples of sea water are used for salinity and oxygen calibration, and for measurements of biogeochemical components that are not reported here. The data were acquired with a Seabird CTD (SBE911+) and an SBE43 for the dissolved oxygen, belonging to the Spanish UTM group. The software SBE data processing was used after decoding and cleaning the raw data. Then, the LPO matlab toolbox was used to calibrate and bin the data as it was done for the previous OVIDE cruises, using on the one hand pre and post-cruise calibration results for the pressure and temperature sensors (done at Ifremer) and on the other hand the water samples of the 24 bottles of the rosette at each station for the salinity and dissolved oxygen data. A final accuracy of 0.002°C, 0.002 psu and 0.04 ml/l (2.3 umol/kg) was obtained on final profiles of temperature, salinity and dissolved oxygen, compatible with international requirements issued from the WOCE program.

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This article is concerned with the construction of general isotropic and anisotropic adaptive strategies, as well as hp-mesh refinement techniques, in combination with dual-weighted-residual a posteriori error indicators for the discontinuous Galerkin finite element discretization of compressible fluid flow problems.

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Thesis (Ph.D, Mechanical and Materials Engineering) -- Queen's University, 2016-08-31 09:37:50.239

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Fluids are important because of their preponderance in our lives. Fluid mechanics touches almost every aspect of our daily lives, and it plays a central role in many branches of science and technology. Therefore, it is a challenging and exciting field of scientific activity due to the complexity of the subject studied and the breadth of the applications. The quest for advances in fluid mechanics, as in other scientific fields, emerge from analytical, computational (CFD) and experimental studies. The improvement in our ability to describe, predict and control the phenomena played (and plays) key roles in the technological breakthroughs. The present theme issue of “Fluid and Heat Flow: Simulation and Optimization” collects a selection of papers. selection of papers presented at Special Session “Fluid Flow, Energy Transfer and Design”

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Changes in fluidization behaviour behaviour was characterised for parallelepiped particles with three aspect ratios, 1:1, 2:1 and 3:1 and spherical particles. All drying experiments were conducted at 500C and 15 % RH using a heat pump dehumidifier system. Fluidization experiments were undertaken for the bed heights of 100, 80, 60 and 40 mm and at 10 moisture content levels. Due to irregularities in shape minimum fluidisation velocity of parallelepiped particulates (potato) could not fitted to any empirical model. Also a generalized equation was used to predict minimum fluidization velocity. The modified quasi-stationary method (MQSM) has been proposed to describe drying kinetics of parallelepiped particulates at 30o C, 40o C and 50o C that dry mostly in the falling rate period in a batch type fluid bed dryer.

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Monitoring unused or dark IP addresses offers opportunities to extract useful information about both on-going and new attack patterns. In recent years, different techniques have been used to analyze such traffic including sequential analysis where a change in traffic behavior, for example change in mean, is used as an indication of malicious activity. Change points themselves say little about detected change; further data processing is necessary for the extraction of useful information and to identify the exact cause of the detected change which is limited due to the size and nature of observed traffic. In this paper, we address the problem of analyzing a large volume of such traffic by correlating change points identified in different traffic parameters. The significance of the proposed technique is two-fold. Firstly, automatic extraction of information related to change points by correlating change points detected across multiple traffic parameters. Secondly, validation of the detected change point by the simultaneous presence of another change point in a different parameter. Using a real network trace collected from unused IP addresses, we demonstrate that the proposed technique enables us to not only validate the change point but also extract useful information about the causes of change points.

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Two-stroke outboard boat engines using total loss lubrication deposit a significant proportion of their lubricant and fuel directly into the water. The purpose of this work is to document the velocity and concentration field characteristics of a submerged swirling water jet emanating from a propeller in order to provide information on its fundamental characteristics. Measurements of the velocity and concentration field were performed in a turbulent jet generated by a model boat propeller (0.02 m diameter) operating at 1500 rpm and 3000 rpm. The measurements were carried out in the Zone of Established Flow up to 50 propeller diameters downstream of the propeller. Both the mean axial velocity profile and the mean concentration profile showed self-similarity. Further, the stand deviation growth curve was linear. The effects of propeller speed and dye release location were also investigated.

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One of the new challenges in aeronautics is combining and accounting for multiple disciplines while considering uncertainties or variability in the design parameters or operating conditions. This paper describes a methodology for robust multidisciplinary design optimisation when there is uncertainty in the operating conditions. The methodology, which is based on canonical evolution algorithms, is enhanced by its coupling with an uncertainty analysis technique. The paper illustrates the use of this methodology on two practical test cases related to Unmanned Aerial Systems (UAS). These are the ideal candidates due to the multi-physics involved and the variability of missions to be performed. Results obtained from the optimisation show that the method is effective to find useful Pareto non-dominated solutions and demonstrate the use of robust design techniques.