987 resultados para soft-commutation techniques


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Strontium-modified lead titanate thin films with composition Pb1-xSrxTiO3 were grown on Pt/Ti/SiO2/Si substrates using the polymeric precursor method. The structural phase evolution as a function of the Sr contents was studied using micro-Raman scattering, specular reflectance infrared Fourier transform spectroscopy, and x-ray diffraction. The results showed a gradual change from tetragonal to cubic structure, the transition occurring at about x = 0.58. The infrared reflectance spectra showed that the frequency of several peaks decreases as the strontium concentration increases. These features are correlated with a decrease in the tetragonal distortion of the TiO6 octahedra as the strontium concentration increases.

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This paper presents a novel single-phase high power factor PWM boost rectifier, featuring soft commutation of the active switches at zero-current (ZCS). It incorporates the most desirable properties of the conventional PWM and the soft-switching resonant techniques. The input current shaping is achieved with average current mode control, and continuous inductor current mode. This new PWM converter provides ZCS turn-on and turn-off of the active switches, and it is suitable for high power applications employing IGBTs. Principle of operation, theoretical analysis, a design example, and experimental results from a laboratory prototype rated at 1600 W with 400 Vdc output voltage are presented. The measured efficiency and power factor were 96.2% and 0.99 respectively, with an input current THD equal to 3.94%, for an input voltage THD equal to 3.8%, at rated load.

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This article argues that for all its efforts to implement soft power techniques, the Kremlin still fails to grasp the subtle, voluntaristic essence of soft power. This is reflected in a style of public interaction that has practical implications for how Russian soft power overtures are received by the audience. This is demonstrated through the findings of mixed-method empirical research from four Ukrainian regions. Thus, while surveys show that the worldview promoted by Russian public diplomacy resonates to some extent, insights from focus groups indicate that potential attraction is nevertheless limited by Russia's 'hard' and obtrusive approach to cultural influence.

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Accurate estimation of road pavement geometry and layer material properties through the use of proper nondestructive testing and sensor technologies is essential for evaluating pavement’s structural condition and determining options for maintenance and rehabilitation. For these purposes, pavement deflection basins produced by the nondestructive Falling Weight Deflectometer (FWD) test data are commonly used. The nondestructive FWD test drops weights on the pavement to simulate traffic loads and measures the created pavement deflection basins. Backcalculation of pavement geometry and layer properties using FWD deflections is a difficult inverse problem, and the solution with conventional mathematical methods is often challenging due to the ill-posed nature of the problem. In this dissertation, a hybrid algorithm was developed to seek robust and fast solutions to this inverse problem. The algorithm is based on soft computing techniques, mainly Artificial Neural Networks (ANNs) and Genetic Algorithms (GAs) as well as the use of numerical analysis techniques to properly simulate the geomechanical system. A widely used pavement layered analysis program ILLI-PAVE was employed in the analyses of flexible pavements of various pavement types; including full-depth asphalt and conventional flexible pavements, were built on either lime stabilized soils or untreated subgrade. Nonlinear properties of the subgrade soil and the base course aggregate as transportation geomaterials were also considered. A computer program, Soft Computing Based System Identifier or SOFTSYS, was developed. In SOFTSYS, ANNs were used as surrogate models to provide faster solutions of the nonlinear finite element program ILLI-PAVE. The deflections obtained from FWD tests in the field were matched with the predictions obtained from the numerical simulations to develop SOFTSYS models. The solution to the inverse problem for multi-layered pavements is computationally hard to achieve and is often not feasible due to field variability and quality of the collected data. The primary difficulty in the analysis arises from the substantial increase in the degree of non-uniqueness of the mapping from the pavement layer parameters to the FWD deflections. The insensitivity of some layer properties lowered SOFTSYS model performances. Still, SOFTSYS models were shown to work effectively with the synthetic data obtained from ILLI-PAVE finite element solutions. In general, SOFTSYS solutions very closely matched the ILLI-PAVE mechanistic pavement analysis results. For SOFTSYS validation, field collected FWD data were successfully used to predict pavement layer thicknesses and layer moduli of in-service flexible pavements. Some of the very promising SOFTSYS results indicated average absolute errors on the order of 2%, 7%, and 4% for the Hot Mix Asphalt (HMA) thickness estimation of full-depth asphalt pavements, full-depth pavements on lime stabilized soils and conventional flexible pavements, respectively. The field validations of SOFTSYS data also produced meaningful results. The thickness data obtained from Ground Penetrating Radar testing matched reasonably well with predictions from SOFTSYS models. The differences observed in the HMA and lime stabilized soil layer thicknesses observed were attributed to deflection data variability from FWD tests. The backcalculated asphalt concrete layer thickness results matched better in the case of full-depth asphalt flexible pavements built on lime stabilized soils compared to conventional flexible pavements. Overall, SOFTSYS was capable of producing reliable thickness estimates despite the variability of field constructed asphalt layer thicknesses.

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Four hybrid algorithms has been developed for the solution of the unit commitment problem. They use simulated annealing as one of the constituent techniques, and produce lower cost schedules; two of them have less overhead than other soft computing techniques. They are also more robust to the choice of parameters. A special technique avoids the generating of infeasible schedules, and thus reduces computation time.

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This talk addresses the problem of controlling a heating ventilating and air conditioning system with the purpose of achieving a desired thermal comfort level and energy savings. The formulation uses the thermal comfort, assessed using the predicted mean vote (PMV) index, as a restriction and minimises the energy spent to comply with it. This results in the maintenance of thermal comfort and on the minimisation of energy, which in most operating conditions are conflicting goals requiring some sort of optimisation method to find appropriate solutions over time. In this work a discrete model based predictive control methodology is applied to the problem. It consists of three major components: the predictive models, implemented by radial basis function neural networks identifed by means of a multi-objective genetic algorithm [1]; the cost function that will be optimised to minimise energy consumption and provide adequate thermal comfort; and finally the optimisation method, in this case a discrete branch and bound approach. Each component will be described, with a special emphasis on a fast and accurate computation of the PMV indices [2]. Experimental results obtained within different rooms in a building of the University of Algarve will be presented, both in summer [3] and winter [4] conditions, demonstrating the feasibility and performance of the approach. Energy savings resulting from the application of the method are estimated to be greater than 50%.

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The IFAC International Conference on Intelligent Control Systems and Signal Processing (ICONS 2003) was organized under the auspices of the recently founded IFAC Technical Committee on Cognition and Control, and it was the first IFAC event specifically devoted to this theme. Recognizing the importance of soft-computing techniques for fields covered by other IFAC Technical Committees, ICONS 2003 was a multi-track Conference, co-sponsored by four additional Technical Committees: Computers for Control, Optimal Control, Control in Agriculture, and Modelling, Identification and Signal Processing. The Portuguese Society for Automatic Control (APCA) hosted ICONS 2003, which was held at the University of Algarve, Faro, Portugal.

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Polydimethylsiloxane (PDMS) is the elastomer of choice to create a variety of microfluidic devices by soft lithography techniques (eg., [1], [2], [3], [4]). Accurate and reliable design, manufacture, and operation of microfluidic devices made from PDMS, require a detailed characterization of the deformation and failure behavior of the material. This paper discusses progress in a recently-initiated research project towards this goal. We have conducted large-deformation tension and compression experiments on traditional macroscale specimens, as well as microscale tension experiments on thin-film (≈ 50µm thickness) specimens of PDMS with varying ratios of monomer:curing agent (5:1, 10:1, 20:1). We find that the stress-stretch response of these materials shows significant variability, even for nominally identically prepared specimens. A non-linear, large-deformation rubber-elasticity model [5], [6] is applied to represent the behavior of PDMS. The constitutive model has been implemented in a finite-element program [7] to aid the design of microfluidic devices made from this material. As a first attempt towards the goal of estimating the non-linear material parameters for PDMS from indentation experiments, we have conducted micro-indentation experiments using a spherical indenter-tip, and carried out corresponding numerical simulations to verify how well the numerically-predicted P(load-h(depth of indentation) curves compare with the corresponding experimental measurements. The results are encouraging, and show the possibility of estimating the material parameters for PDMS from relatively simple micro-indentation experiments, and corresponding numerical simulations.

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The Kagome lattice, comprising a two-dimensional array of corner-sharing equilateral triangles, is central to the exploration of magnetic frustration. In such a lattice, antiferromagnetic coupling between ions in triangular plaquettes prevents all of the exchange interactions being simultaneously satisfied and a variety of novel magnetic ground states may result at low temperature. Experimental realization of a Kagome lattice remains difficult. The jarosite family of materials of nominal composition AM3(SO4)2(OH)6 (A = monovalent cation; M= Fe3+, Cr3+), offers perhaps one of the most promising manifestations of the phenomenon of magnetic frustration in two dimensions. The magnetic properties of jarosites are however extremely sensitive to the degree of coverage of magnetic sites. Consequently, there is considerable interest in the use of soft chemical techniques for the design and synthesis of novel materials in which to explore the effects of spin, degree of site coverage and connectivity on magnetic frustration.

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Market failure can be corrected using different regulatory approaches ranging from high to low intervention. Recently, classic regulations have been criticized as costly and economically irrational and thus policy makers are giving more consideration to soft regulatory techniques such as information remedies. However, despite the plethora of food information conveyed by different media there appears to be a lack of studies exploring how consumers evaluate this information and how trust towards publishers influence their choices for food information. In order to fill such a gap, this study investigates questions related to topics which are more relevant to consumers, who should disseminate trustful food information, and how communication should be conveyed and segmented. Primary data were collected both through qualitative (in depth interviews and focus groups) and quantitative research (web and mail surveys). Attitudes, willingness to pay for food information and trust towards public and private sources conveying information through a new food magazine were assessed using both multivariate statistical methods and econometric analysis. The study shows that consumer attitudes towards food information topics can be summarized along three cognitive-affective dimensions: the agro-food system, enjoyment and wellness. Information related to health risks caused by nutritional disorders and food safety issues caused by bacteria and chemical substances is the most important for about 90% of respondents. Food information related to regulations and traditions is also considered important for more than two thirds of respondents, while information about food production and processing techniques, life style and food fads are considered less important by the majority of respondents. Trust towards food information disseminated by public bodies is higher than that observed for private bodies. This behavior directly affects willingness to pay (WTP) for food information provided by public and private publishers when markets are shocked by a food safety incident. WTP for consumer association (€ 1.80) and the European Food Safety Authority (€ 1.30) are higher than WTP for the independent and food industry publishers which cluster around zero euro. Furthermore, trust towards the type of publisher also plays a key role in food information market segmentation together with socio-demographic and economic variables such as gender, age, presence of children and income. These findings invite policy makers to reflect on the possibility of using information remedies conveyed using trusted sources of information to specific segments of consumers as an interesting soft alternative to the classic way of regulating modern food markets.

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In this paper we propose an innovative approach for behaviour recognition, from a multicamera environment, based on translating video activity into semantics. First, we fuse tracks from individual cameras through clustering employing soft computing techniques. Then, we introduce a higher-level module able to translate fused tracks into semantic information. With our proposed approach, we address the challenge set in PETS 2014 on recognising behaviours of interest around a parked vehicle, namely the abnormal behaviour of someone walking around the vehicle.

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Microfluidics has the potential to enhance the understanding of the biological fluids under strain, due to the laminar nature of the fluid and the possibility to mimic the real conditions. We present advances on charaterization of a microfluidic platform to study high strain rate flows in the transport of biological fluids. These advances are improvements on the reproduction of a  constant extensional strain rate using micro contractions and development of 3D numerical models. The micro geometries have been fabricated in polydimethyl siloxame (PDMS) using standard soft-lithography techniques with a photolithographically patterned mold. A comparison of some microcontractions with different funnel characteristics is presented. The Micro Particle Image Velocimetry technique has been applied to validate the numerical simulations. We demonstrate the use of microfluidics in the reproduction of a large range of controllable extensional strains that can be used in the study of the effect of flow on biological fluids.

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Biological fluids such as blood, proteins and DNA solutiosn moving within fluidic channels can potentially be exposed to high level of shear, extension or mixed stress, either in vitro such as industrial processing of blood products or in vivo such as ocurrs in some pathological conditions. This exposure to a high level of strain can trigger some reactions. In most of the cases the nature of the flow is mixed with shear and extensional components. The ability ot isolate the effects of each component is critical in order to understand the mechanisms behind the reactions and potentially prevent them. Applying hydrodynamic flow focusing, we present in this investigation the characterization of microchannels that allow study of the regions of high shear or high extension strain rate. Micro channels were fabricated in polydimethyl siloxane (PDMS)  using standard soft-lithography techniques with a photolithographically patterned mold. Characterization of the regions with high shear and high extension strain rate is presented. Computational Fluid Dynamics (CFD) simulations in three dimensions have been carried out to gain more detailed local flow information, and the results have been validated experimentally. A comparison between the numerical models and experiment and is presented. The advantages of microfluidic flow focusing in the study  of the effects of shear and extension strain rates for biological fluids are outlined.

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This paper describes the design, simulation, fabrication and experimental analysis of a passive micromixer for the mixing of biological solvents. The mixer consists of a T-junction, followed by a serpentine microchannel. the serpentine has three arcs, each equipped with circular barriers that are patterned as two opposing triangles. >The barriers are engineered to induce periodic perturbations in the flow field and enhance the mixing. CFD (Computational Fluid Dynamics) method is applied to optimise the geometric variables of the mixer before fabrication. The mixer is made from PDMS (Polydimethylsiloxane) using photo- and soft-lithography techniques. Experimental measurements are performed using yellow and blue food dyes as the mixing fluids. The mixing is measured by analysing the composition of the flow's colour across the outlet channel. The performance of the mixer is examined in a wide range of flow rates from 0.5 to 10 µl/min. Mixing efficiencies of higher than 99.4% are obtained in the experiments confirming the results of numerical simulations. The proposed mixer can be employed as a part of lab-on-a-chip for biomedical applications.