940 resultados para Parallel hot-wire method


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The structure of a turbulent non-premixed flame of a biogas fuel in a hot and diluted coflow mimicking moderate and intense low dilution (MILD) combustion is studied numerically. Biogas fuel is obtained by dilution of Dutch natural gas (DNG) with CO2. The results of biogas combustion are compared with those of DNG combustion in the Delft Jet-in-Hot-Coflow (DJHC) burner. New experimental measurements of lift-off height and of velocity and temperature statistics have been made to provide a database for evaluating the capability of numerical methods in predicting the flame structure. Compared to the lift-off height of the DNG flame, addition of 30 % carbon dioxide to the fuel increases the lift-off height by less than 15 %. Numerical simulations are conducted by solving the RANS equations using Reynolds stress model (RSM) as turbulence model in combination with EDC (Eddy Dissipation Concept) and transported probability density function (PDF) as turbulence-chemistry interaction models. The DRM19 reduced mechanism is used as chemical kinetics with the EDC model. A tabulated chemistry model based on the Flamelet Generated Manifold (FGM) is adopted in the PDF method. The table describes a non-adiabatic three stream mixing problem between fuel, coflow and ambient air based on igniting counterflow diffusion flamelets. The results show that the EDC/DRM19 and PDF/FGM models predict the experimentally observed decreasing trend of lift-off height with increase of the coflow temperature. Although more detailed chemistry is used with EDC, the temperature fluctuations at the coflow inlet (approximately 100K) cannot be included resulting in a significant overprediction of the flame temperature. Only the PDF modeling results with temperature fluctuations predict the correct mean temperature profiles of the biogas case and compare well with the experimental temperature distributions.

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Rotational moulding is a method to produce hollow plastic articles. Heating is normally carried out by placing the mould into a hot air oven where the plastic material in the mould is heated. The most common cooling media are water and forced air. Due to the inefficient nature of conventional hot air ovens most of the energy supplied by the oven does not go to heat the plastic and as a consequence the procedure has very long cycle times. Direct oil heating is an effective alternative in order to achieve better energy efficiency and cycle times. This research work has combined this technology with new innovative design of mould, applying the advantages of electroforming and rapid prototyping. Complex cavity geometries are manufactured by electroforming from a rapid prototyping mandrel. The approach involves conformal heating and cooling channels , where the oil flows into a parallel channel to the electroformed cavity (nickel or copper). Because of this the mould enables high temperature uniformity with direct heating and cooling of the electroformed shell, Uniform heating and cooling is important not only for good quality parts but also for good uniform wall thickness distribution in the rotationally moulded part. The experimental work with the manufactured prototype mould has enabled analysis of the thermal uniformity in the cavity, under different temperatures. Copyright © 2008 by ASME.

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[EN]The increasing use of microstrip technology require more accurate analysis methods like full wave method of moments. However, this involves a great computational effort. To reduce the computation time, an alternative parallel method to analyze irregular microstrip structures is presented in this paper. This method calculates the unknown surface current on the planar structure trough a irregular rectangular division using basis and weighted functions. The parallel algorithm performs the calculus of a [Z] matrix and then solves the system using current densities as the unknowns. This parallel program was implemented in the IBM-SP2 using MPI library.

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A parallel method for the dynamic partitioning of unstructured meshes is outlined. The method includes diffusive load-balancing techniques and an iterative optimisation technique known as relative gain optimisationwhich both balances theworkload and attempts to minimise the interprocessor communications overhead. It can also optionally include amultilevel strategy. Experiments on a series of adaptively refined meshes indicate that the algorithmprovides partitions of an equivalent or higher quality to static partitioners (which do not reuse the existing partition) and much more rapidly. Perhaps more importantly, the algorithm results in only a small fraction of the amount of data migration compared to the static partitioners.

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This chapter describes a parallel optimization technique that incorporates a distributed load-balancing algorithm and provides an extremely fast solution to the problem of load-balancing adaptive unstructured meshes. Moreover, a parallel graph contraction technique can be employed to enhance the partition quality and the resulting strategy outperforms or matches results from existing state-of-the-art static mesh partitioning algorithms. The strategy can also be applied to static partitioning problems. Dynamic procedures have been found to be much faster than static techniques, to provide partitions of similar or higher quality and, in comparison, involve the migration of a fraction of the data. The method employs a new iterative optimization technique that balances the workload and attempts to minimize the interprocessor communications overhead. Experiments on a series of adaptively refined meshes indicate that the algorithm provides partitions of an equivalent or higher quality to static partitioners (which do not reuse the existing partition) and much more quickly. The dynamic evolution of load has three major influences on possible partitioning techniques; cost, reuse, and parallelism. The unstructured mesh may be modified every few time-steps and so the load-balancing must have a low cost relative to that of the solution algorithm in between remeshing.

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This paper describes an parallel semi-Lagrangian finite difference approach to the pricing of early exercise Asian Options on assets with a stochastic volatility. A multigrid procedure is described for the fast iterative solution of the discrete linear complementarity problems that result. The accuracy and performance of this approach is improved considerably by a strike-price related analytic transformation of asset prices. Asian options are contingent claims with payoffs that depend on the average price of an asset over some time interval. The payoff may depend on this average and a fixed strike price (Fixed Strike Asians) or it may depend on the average and the asset price (Floating Strike Asians). The option may also permit early exercise (American contract) or confine the holder to a fixed exercise date (European contract). The Fixed Strike Asian with early exercise is considered here where continuous arithmetic averaging has been used. Pricing such an option where the asset price has a stochastic volatility leads to the requirement to solve a tri-variate partial differential inequation in the three state variables of asset price, average price and volatility (or equivalently, variance). The similarity transformations [6] used with Floating Strike Asian options to reduce the dimensionality of the problem are not applicable to Fixed Strikes and so the numerical solution of a tri-variate problem is necessary. The computational challenge is to provide accurate solutions sufficiently quickly to support realtime trading activities at a reasonable cost in terms of hardware requirements.

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A parallel method for dynamic partitioning of unstructured meshes is described. The method employs a new iterative optimisation technique which both balances the workload and attempts to minimise the interprocessor communications overhead. Experiments on a series of adaptively refined meshes indicate that the algorithm provides partitions of an equivalent or higher quality to static partitioners (which do not reuse the existing partition) and much more quickly. Perhaps more importantly, the algorithm results in only a small fraction of the amount of data migration compared to the static partitioners.

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A parallel method for the dynamic partitioning of unstructured meshes is described. The method introduces a new iterative optimisation technique known as relative gain optimisation which both balances the workload and attempts to minimise the interprocessor communications overhead. Experiments on a series of adaptively refined meshes indicate that the algorithm provides partitions of an equivalent or higher quality to static partitioners (which do not reuse the existing partition) and much more rapidly. Perhaps more importantly, the algorithm results in only a small fraction of the amount of data migration compared to the static partitioners.

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Aquaculture has been expanded rapidly to become a major commercial and food-producing sector worldwide in recent decade. In parallel, viral diseases rapidly spread among farms causing enormous economic losses. The accurate detection of pathogens at early stages of infection is a key point for disease control in aquaculture. Spring Viraemia of Carp Virus (SVCV) is a very severe pathogen of carp fishes in different parts of the world and is categorized as a reportable listed disease in the annual published list of World Organization for animal Health (OIE). The objective of this study was to develop and evaluate RT- PCR test for detecting SVC virus and also the sensitivity and specificity of this test. A semi nested RT- PCR was designed using combination of three primers: two external (SVCF , SVCR) and one internal (SVCS) primers which based on conserved region of G gen. The specificity of designed primers (only external ones) by examination on Viral Hemorrhagic Septicemia Virus (VHSV) and Infectious Hematopoietic Necrosis Virus (IHNV) was confirmed. For optimizing of the PCR test, primer concentration, primer annealing temperature, cycle number and Mgcl2 concentration were surveyed. Also for validity test, prevention of false negative and Assurance of its accuracy, a competitive internal control (mimic) designed and its suitable concentration was defined. Evaluation of the sensitivity of designed test were conducted first by comparing the different commercially available RNA isolation guidelines, two guidelines: isotiocyanate phenol–chloroform based protocols (RNX–Plus Iran, Iq2000 kit Taiwan ) and two column based protocols (Cinna pure RNA Iran , high pure viral RNA kit, Roche Germany ). The results indicated that the column based protocols (Roche method and Cinna pure), yield 36.77 ng/μl and 16/47 ng/μl RNA concentration respectively, which were significantly higher than other protocols(P<0.05). Then for evaluation of extracted RNA sensitivity, Serial dilution of SVCV strain 56.70 grown in EPC (1.9×105 TCID50/ml) was examined To compare sensitivity. Extracted RNA from serial dilution with stone's primers and commercial IQ-2000 kit were examined simultaneously. The result indicated that designed semi- nested RT- PCR was able to recognize SVC virus to 10-4 dilution and stone's primer recognize to 10-3 dilution whereas Iq-2000 commercial kit did not recognized in any dilution. In high virus titer in designed test two DNA band (462 bp and 266 bp) produced, and by decreasing virus titer 462 bp was omitted. In low virus titer or lack of virus, just DNA band (mimic) 729 bp can propagate. After designing and optimizing PCR test, a total of 400 suspected cultured Cyprinus carpio with high mortality from 4 aquaculture zone of Khuzestan province were collected and tested for SVCV during 2012- 2013 using developed PCR method and IQ- 2000. The results indicated that SVC virus was not observed in samples using both methods.

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The research described in this thesis was motivated by the need of a robust model capable of representing 3D data obtained with 3D sensors, which are inherently noisy. In addition, time constraints have to be considered as these sensors are capable of providing a 3D data stream in real time. This thesis proposed the use of Self-Organizing Maps (SOMs) as a 3D representation model. In particular, we proposed the use of the Growing Neural Gas (GNG) network, which has been successfully used for clustering, pattern recognition and topology representation of multi-dimensional data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models, without considering time constraints. It is proposed a hardware implementation leveraging the computing power of modern GPUs, which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). The proposed methods were applied to different problem and applications in the area of computer vision such as the recognition and localization of objects, visual surveillance or 3D reconstruction.

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The overarching theme of this thesis is mesoscale optical and optoelectronic design of photovoltaic and photoelectrochemical devices. In a photovoltaic device, light absorption and charge carrier transport are coupled together on the mesoscale, and in a photoelectrochemical device, light absorption, charge carrier transport, catalysis, and solution species transport are all coupled together on the mesoscale. The work discussed herein demonstrates that simulation-based mesoscale optical and optoelectronic modeling can lead to detailed understanding of the operation and performance of these complex mesostructured devices, serve as a powerful tool for device optimization, and efficiently guide device design and experimental fabrication efforts. In-depth studies of two mesoscale wire-based device designs illustrate these principles—(i) an optoelectronic study of a tandem Si|WO3 microwire photoelectrochemical device, and (ii) an optical study of III-V nanowire arrays.

The study of the monolithic, tandem, Si|WO3 microwire photoelectrochemical device begins with development and validation of an optoelectronic model with experiment. This study capitalizes on synergy between experiment and simulation to demonstrate the model’s predictive power for extractable device voltage and light-limited current density. The developed model is then used to understand the limiting factors of the device and optimize its optoelectronic performance. The results of this work reveal that high fidelity modeling can facilitate unequivocal identification of limiting phenomena, such as parasitic absorption via excitation of a surface plasmon-polariton mode, and quick design optimization, achieving over a 300% enhancement in optoelectronic performance over a nominal design for this device architecture, which would be time-consuming and challenging to do via experiment.

The work on III-V nanowire arrays also starts as a collaboration of experiment and simulation aimed at gaining understanding of unprecedented, experimentally observed absorption enhancements in sparse arrays of vertically-oriented GaAs nanowires. To explain this resonant absorption in periodic arrays of high index semiconductor nanowires, a unified framework that combines a leaky waveguide theory perspective and that of photonic crystals supporting Bloch modes is developed in the context of silicon, using both analytic theory and electromagnetic simulations. This detailed theoretical understanding is then applied to a simulation-based optimization of light absorption in sparse arrays of GaAs nanowires. Near-unity absorption in sparse, 5% fill fraction arrays is demonstrated via tapering of nanowires and multiple wire radii in a single array. Finally, experimental efforts are presented towards fabrication of the optimized array geometries. A hybrid self-catalyzed and selective area MOCVD growth method is used to establish morphology control of GaP nanowire arrays. Similarly, morphology and pattern control of nanowires is demonstrated with ICP-RIE of InP. Optical characterization of the InP nanowire arrays gives proof of principle that tapering and multiple wire radii can lead to near-unity absorption in sparse arrays of InP nanowires.

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In the presented thesis work, the meshfree method with distance fields was coupled with the lattice Boltzmann method to obtain solutions of fluid-structure interaction problems. The thesis work involved development and implementation of numerical algorithms, data structure, and software. Numerical and computational properties of the coupling algorithm combining the meshfree method with distance fields and the lattice Boltzmann method were investigated. Convergence and accuracy of the methodology was validated by analytical solutions. The research was focused on fluid-structure interaction solutions in complex, mesh-resistant domains as both the lattice Boltzmann method and the meshfree method with distance fields are particularly adept in these situations. Furthermore, the fluid solution provided by the lattice Boltzmann method is massively scalable, allowing extensive use of cutting edge parallel computing resources to accelerate this phase of the solution process. The meshfree method with distance fields allows for exact satisfaction of boundary conditions making it possible to exactly capture the effects of the fluid field on the solid structure.

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In modern power electronics equipment, it is desirable to design a low profile, high power density, and fast dynamic response converter. Increases in switching frequency reduce the size of the passive components such as transformers, inductors, and capacitors which results in compact size and less requirement for the energy storage. In addition, the fast dynamic response can be achieved by operating at high frequency. However, achieving high frequency operation while keeping the efficiency high, requires new advanced devices, higher performance magnetic components, and new circuit topology. These are required to absorb and utilize the parasitic components and also to mitigate the frequency dependent losses including switching loss, gating loss, and magnetic loss. Required performance improvements can be achieved through the use of Radio Frequency (RF) design techniques. To reduce switching losses, resonant converter topologies like resonant RF amplifiers (inverters) combined with a rectifier are the effective solution to maintain high efficiency at high switching frequencies through using the techniques such as device parasitic absorption, Zero Voltage Switching (ZVS), Zero Current Switching (ZCS), and a resonant gating. Gallium Nitride (GaN) device technologies are being broadly used in RF amplifiers due to their lower on- resistance and device capacitances compared with silicon (Si) devices. Therefore, this kind of semiconductor is well suited for high frequency power converters. The major problems involved with high frequency magnetics are skin and proximity effects, increased core and copper losses, unbalanced magnetic flux distribution generating localized hot spots, and reduced coupling coefficient. In order to eliminate the magnetic core losses which play a crucial role at higher operating frequencies, a coreless PCB transformer can be used. Compared to the conventional wire-wound transformer, a planar PCB transformer in which the windings are laid on the Printed Board Circuit (PCB) has a low profile structure, excellent thermal characteristics, and ease of manufacturing. Therefore, the work in this thesis demonstrates the design and analysis of an isolated low profile class DE resonant converter operating at 10 MHz switching frequency with a nominal output of 150 W. The power stage consists of a class DE inverter using GaN devices along with a sinusoidal gate drive circuit on the primary side and a class DE rectifier on the secondary side. For obtaining the stringent height converter, isolation is provided by a 10-layered coreless PCB transformer of 1:20 turn’s ratio. It is designed and optimized using 3D Finite Element Method (FEM) tools and radio frequency (RF) circuit design software. Simulation and experimental results are presented for a 10-layered coreless PCB transformer operating in 10 MHz.

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In this thesis, we explore three methods for the geometrico-static modelling of continuum parallel robots. Inspired by biological trunks, tentacles and snakes, continuum robot designs can reach confined spaces, manipulate objects in complex environments and conform to curvilinear paths in space. In addition, parallel continuum manipulators have the potential to inherit some of the compactness and compliance of continuum robots while retaining some of the precision, stability and strength of rigid-links parallel robots. Subsequently, the foundation of our work is performed on slender beam by applying the Cosserat rod theory, appropriate to model continuum robots. After that, three different approaches are developed on a case study of a planar parallel continuum robot constituted of two connected flexible links. We solve the forward and inverse geometrico-static problem namely by using (a) shooting methods to obtain a numerical solution, (b) an elliptic method to find a quasi-analytical solution, and (c) the Corde model to perform further model analysis. The performances of each of the studied methods are evaluated and their limits are highlighted. This thesis is divided as follows. Chapter one gives the introduction on the field of the continuum robotics and introduce the parallel continuum robots that is studied in this work. Chapter two describe the geometrico-static problem and gives the mathematical description of this problem. Chapter three explains the numerical approach with the shooting method and chapter four introduce the quasi-analytical solution. Then, Chapter five introduce the analytic method inspired by the Corde model and chapter six gives the conclusions of this work.

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In this project an optimal pose selection method for the calibration of an overconstrained Cable-Driven Parallel robot is presented. This manipulator belongs to a subcategory of parallel robots, where the classic rigid "legs" are replaced by cables. Cables are flexible elements that bring advantages and disadvantages to the robot modeling. For this reason, there are many open research issues, and the calibration of geometric parameters is one of them. The identification of the geometry of a robot, in particular, is usually called Kinematic Calibration. Many methods have been proposed in the past years for the solution of the latter problem. Although these methods are based on calibration using different kinematic models, when the robot’s geometry becomes more complex, their robustness and reliability decrease. This fact makes the selection of the calibration poses more complicated. The position and the orientation of the endeffector in the workspace become important in terms of selection. Thus, in general, it is necessary to evaluate the robustness of the chosen calibration method, by means, for example, of a parameter such as the observability index. In fact, it is known from the theory, that the maximization of the above mentioned index identifies the best choice of calibration poses, and consequently, using this pose set may improve the calibration process. The objective of this thesis is to analyze optimization algorithms which aim to calculate an optimal choice of poses both in quantitative and qualitative terms. Quantitatively, because it is of fundamental importance to understand how many poses are needed. Not necessarily a greater number of poses leads to a better result. Qualitatively, because it is useful to understand if the selected combination of poses actually gives additional information in the process of the identification of the parameters.