940 resultados para Lagrangian particle tracking method
Resumo:
The paper addresses the problem of autonomous underwater vehicle (AUV) modelling and parameter estimation as a means to predict the dynamic performance of underwater vehicles and thus provide solid guidelines during their design phase. The use of analytical and semi-empirical (ASE) methods to estimate the hydrodynamic derivatives of a popular class of AUVs is discussed. A comparison is done with the results obtained by using computational fluid dynamics to evaluate the bare hull lift force distribution around a fully submerged body. An application is made to the estimation of the hydrodynamic derivatives of the MAYA AUV, an autonomous underwater vehicle developed under a joint Indian-Portuguese project. The estimates obtained were used to predict the turning diameter of the vehicle during sea trials. (C) 2008 Elsevier Ltd. All rights reserved.
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This work discusses the determination of the breathing patterns in time sequence of images obtained from magnetic resonance (MR) and their use in the temporal registration of coronal and sagittal images. The registration is made without the use of any triggering information and any special gas to enhance the contrast. The temporal sequences of images are acquired in free breathing. The real movement of the lung has never been seen directly, as it is totally dependent on its surrounding muscles and collapses without them. The visualization of the lung in motion is an actual topic of research in medicine. The lung movement is not periodic and it is susceptible to variations in the degree of respiration. Compared to computerized tomography (CT), MR imaging involves longer acquisition times and it is preferable because it does not involve radiation. As coronal and sagittal sequences of images are orthogonal to each other, their intersection corresponds to a segment in the three-dimensional space. The registration is based on the analysis of this intersection segment. A time sequence of this intersection segment can be stacked, defining a two-dimension spatio-temporal (2DST) image. The algorithm proposed in this work can detect asynchronous movements of the internal lung structures and lung surrounding organs. It is assumed that the diaphragmatic movement is the principal movement and all the lung structures move almost synchronously. The synchronization is performed through a pattern named respiratory function. This pattern is obtained by processing a 2DST image. An interval Hough transform algorithm searches for synchronized movements with the respiratory function. A greedy active contour algorithm adjusts small discrepancies originated by asynchronous movements in the respiratory patterns. The output is a set of respiratory patterns. Finally, the composition of coronal and sagittal image pairs that are in the same breathing phase is realized by comparing of respiratory patterns originated from diaphragmatic and upper boundary surfaces. When available, the respiratory patterns associated to lung internal structures are also used. The results of the proposed method are compared with the pixel-by-pixel comparison method. The proposed method increases the number of registered pairs representing composed images and allows an easy check of the breathing phase. (C) 2010 Elsevier Ltd. All rights reserved.
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Aluminum white dross is a valuable material principally due to its high metallic aluminum content. The aim of this work is to develop a method for quantitative analysis of aluminum white dross with high accuracy. Initially, the material was separated into four granulometric fractions by means of screening. Two samples of each fraction were obtained, which were analyzed by means of X-ray fluorescence and energy dispersive spectroscopy in order to determine the elements present in the samples. The crystalline phases aluminum, corundum, spinel, defect spinel, diaoyudaoite, aluminum nitride, silicon and quartz low were identified by X-ray diffraction. The quantitative phase analysis was performed by fitting the X-ray diffraction profile with the Rietveld method using the GSAS software. The following quantitative results were found: 77.8% aluminum, 7.3% corundum, 2.6% spinel, 7.6% defect spinel, 1.8% diaoyudaoite, 2.9% aluminum nitride, and values not significant of quartz and silicon.
Resumo:
High-density polyethylene resins have increasingly been used in the production of pipes for water- and gas-pressurized distribution systems and are expected to remain in service for several years, but they eventually fail prematurely by creep fracture. Usual standard methods used to rank resins in terms of their resistance to fracture are expensive and non-practical for quality control purposes, justifying the search for alternative methods. Essential work of fracture (EWF) method provides a relatively simple procedure to characterize the fracture behavior of ductile polymers, such as polyethylene resins. In the present work, six resins were analyzed using the EWF methodology. The results show that the plastic work dissipation factor, beta w(p), is the most reliable parameter to evaluate the performance. Attention must be given to specimen preparation that might result in excessive dispersion in the results, especially for the essential work of fracture w(e).
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Ni-doped SnO(2) nanoparticles prepared by a polymer precursor method have been characterized structurally and magnetically. Ni doping (up to 10 mol%) does not significantly affect the crystalline structure of SnO(2), but stabilizes smaller particles as the Ni content is increased. A notable solid solution regime up to similar to 3 mol% of Ni, and a Ni surface enrichment for the higher Ni contents are found. The room temperature ferromagnetism with saturation magnetization (MS) similar to 1.2 x 10(-3) emu g(-1) and coercive field (H(C)) similar to 40 Oe is determined for the undoped sample, which is associated with the exchange coupling of the spins of electrons trapped in oxygen vacancies, mainly located on the surface of the particles. This ferromagnetism is enhanced as the Ni content increases up to similar to 3 mol%, where the Ni ions are distributed in a solid solution. Above this Ni content, the ferromagnetism rapidly decays and a paramagnetic behavior is observed. This finding is assigned to the increasing segregation of Ni ions (likely formed by interstitials Ni ions and nearby substitutional sites) on the particle surface, which modifies the magnetic behavior by reducing the available oxygen vacancies and/or the free electrons and favoring paramagnetic behavior.
Resumo:
A polymer precursor method has been used to synthesize Ni-doped SnO(2) nanoparticles. X-ray diffraction (XRD) data analyses indicate the exclusive formation of nanosized particles with rutile-type phase (tetragonal SnO(2)) for Ni contents below 10 mol%. In this concentration range, the particle sizes decrease with increasing Ni content and a bulk solid solution limit was determined at similar to 1 mol%. Ni surface enrichment is present at concentrations higher than the solution limit. Only above 10 mol% Ni. the formation of a second NiO-related phase has been determined. Magnetization measurements suggest the occurrence of ferromagnetism for samples in the solid solution regime (below similar to 1 mol%). This ferromagnetism is associated with the exchange interaction between electron spins trapped on oxygen vacancies, and is enhanced as the amount of Ni(2+) substituting at Sn(4+) sites increases. Above the solid solution limit, ferromagnetism is destroyed by the Ni surface enrichment and the system behaves as a paramagnet. (C) 2010 Elsevier B.V. All rights reserved.
Resumo:
The effect of different precracking methods on the results of linear elastic K(Ic) fracture toughness testing with medium-density polyethylene (MDPE) was investigated. Cryogenic conditions were imposed in order to obtain valid K(Ic) values from specimens of suitable size. Most conservative K(Ic) values were obtained by slow pressing a fresh razor blade at the notch root of the specimen. Due to the low deformation level imposed on the crack tip region, the slow pressing razor blade technique also produced less scatter in fracture toughness results. It has been shown that the slow stable crack growth preceding catastrophic brittle failure during K(Ic) tests in MOPE under cryogenic conditions should not be disregarded as it has relevant physical meaning and may affect the fracture toughness results. (C) 2010 Elsevier Ltd. All rights reserved.
Resumo:
The Cluster Variation Method (CVM), introduced over 50 years ago by Prof. Dr. Ryoichi Kikuchi, is applied to the thermodynamic modeling of the BCC Cr-Fe system in the irregular tetrahedron approximation, using experimental thermochemical data as initial input for accessing the model parameters. The results are checked against independent data on the low-temperature miscibility gap, using increasingly accurate thermodynamic models, first by the inclusion of the magnetic degrees of freedom of iron and then also by the inclusion of the magnetic degrees of freedom of chromium. It is shown that a reasonably accurate description of the phase diagram at the iron-rich side (i.e. the miscibility gap borders and the Curie line) is obtained, but only at expense of the agreement with the above mentioned thermochemical data. Reasons for these inconsistencies are discussed, especially with regard to the need of introducing vibrational degrees of freedom in the CVM model. (C) 2008 Elsevier Ltd. All rights reserved.
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The aim of this work is to study MnO reduction by solid carbon. The influence of size of carbon particles, slag basicity, and bath temperature on MnO reduction was investigated. Fine Manganese ore particles were used as a source of MnO. Three sizes of carbon particles were used; 0.230 mm, 0.162 mm and 0.057 mm, binary basicity of 1 and 1.5 and temperatures of 1550, 1550 and 1600 degrees C. Curves were drawn for Mn content in the bath as a function of time and temperature for the several studied parameters. The MnO reduction rates were determined using these data. [doi:10.2320/matertrans.M2011007]
Resumo:
In the present work, the sensitivity of NIR spectroscopy toward the evolution of particle size was studied during emulsion homopolymerization of styrene (Sty) and emulsion copolymerization of vinyl acetate-butyl acrylate conducted in a semibatch stirred tank and a tubular pulsed sieve plate reactor, respectively. All NIR spectra were collected online with a transflectance probe immersed into the reaction medium. The spectral range used for the NIR monitoring was from 9 500 to 13 000 cm(-1), where the absorbance of the chemical components present is minimal and the changes in the NIR spectrum can be ascribed to the effects of light scattering by the polymer particles. Off-line measurements of the average diameter of the polymer particles by DLS were used as reference values for the development of the multi-variate NIR calibration models based on partial least squares. Results indicated that, in the spectral range studied, it is possible to monitor the evolution of the average size of the polymer particles during emulsion polymerization reactions. The inclusion of an additional spectral range, from 5 701 to 6 447 cm(-1), containing information on absorbances (""chemical information"") in the calibration models was also evaluated.
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In this work, a stable MPC that maximizes the domain of attraction of the closed-loop system is proposed. The proposed approach is suitable to real applications in the sense that it accounts for the case of output tracking, it is offset free if the output target is reachable and minimizes the offset if some of the constraints are active at steady state. The new approach is based on the definition of a Minkowski functional related to the input and terminal constraints of the stable infinite horizon MPC. It is also shown that the domain of attraction is defined by the system model and the constraints, and it does not depend on the controller tuning parameters. The proposed controller is illustrated with small order examples of the control literature. (C) 2011 Elsevier Ltd. All rights reserved.
Resumo:
This work presents a mathematical model for the vinyl acetate and n-butyl acrylate emulsion copolymerization process in batch reactors. The model is able to explain the effects of simultaneous changes in emulsifier concentration, initiator concentration, monomer-to-water ratio, and monomer feed composition on monomer conversion, copolymer composition and, to lesser extent, average particle size evolution histories. The main features of the system, such as the increase in the rate of polymerization as temperature, emulsifier, and initiator concentrations increase are correctly represented by the model. The model accounts for the basic features of the process and may be useful for practical applications, despite its simplicity and a reduced number of adjustable parameters.
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This paper deals with the problem of tracking target sets using a model predictive control (MPC) law. Some MPC applications require a control strategy in which some system outputs are controlled within specified ranges or zones (zone control), while some other variables - possibly including input variables - are steered to fixed target or set-point. In real applications, this problem is often overcome by including and excluding an appropriate penalization for the output errors in the control cost function. In this way, throughout the continuous operation of the process, the control system keeps switching from one controller to another, and even if a stabilizing control law is developed for each of the control configurations, switching among stable controllers not necessarily produces a stable closed loop system. From a theoretical point of view, the control objective of this kind of problem can be seen as a target set (in the output space) instead of a target point, since inside the zones there are no preferences between one point or another. In this work, a stable MPC formulation for constrained linear systems, with several practical properties is developed for this scenario. The concept of distance from a point to a set is exploited to propose an additional cost term, which ensures both, recursive feasibility and local optimality. The performance of the proposed strategy is illustrated by simulation of an ill-conditioned distillation column. (C) 2010 Elsevier Ltd. All rights reserved.
Resumo:
The kinetics and mechanism of the thermal activation of peroxydisulfate, in the temperature range from 60 to 80 degrees C, was investigated in the presence and absence of sodium formate as an additive to turn the oxidizing capacity of the reaction mixture into a reductive one. Trichloroacetic acid, TCA, whose degradation by a reductive mechanism is well reported in the literature, was used as a probe. The chemistry of thermally activated peroxydisulfate is described by a reaction scheme involving free radical generation. The proposed mechanism is evaluated by a computer simulation of the concentration profiles obtained under different experimental conditions. In the presence of formate, SO(4)(center dot-) radicals yield CO(2)(center dot-), which are the main species available for degrading TCA. Under the latter conditions, TCA is more efficiently depleted than in the absence of formate, but otherwise identical conditions of temperature and [S(2)O(8)(2-)]. We therefore conclude that activated peroxydisulfate in the presence of formate as an additive is a convenient method for the mineralization of substrates that are refractory to oxidation. such as perchlorinated hydrocarbons and TCA. This method has the advantage that leaves no toxic residues. (C) 2009 Elsevier Ltd. All rights reserved.
Resumo:
As is well known, Hessian-based adaptive filters (such as the recursive-least squares algorithm (RLS) for supervised adaptive filtering, or the Shalvi-Weinstein algorithm (SWA) for blind equalization) converge much faster than gradient-based algorithms [such as the least-mean-squares algorithm (LMS) or the constant-modulus algorithm (CMA)]. However, when the problem is tracking a time-variant filter, the issue is not so clear-cut: there are environments for which each family presents better performance. Given this, we propose the use of a convex combination of algorithms of different families to obtain an algorithm with superior tracking capability. We show the potential of this combination and provide a unified theoretical model for the steady-state excess mean-square error for convex combinations of gradient- and Hessian-based algorithms, assuming a random-walk model for the parameter variations. The proposed model is valid for algorithms of the same or different families, and for supervised (LMS and RLS) or blind (CMA and SWA) algorithms.