985 resultados para Identification parameters


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Void fraction sensors are important instruments not only for monitoring two-phase flow, but for furnishing an important parameter for obtaining flow map pattern and two-phase flow heat transfer coefficient as well. This work presents the experimental results obtained with the analysis of two axially spaced multiple-electrode impedance sensors tested in an upward air-water two-phase flow in a vertical tube for void fraction measurements. An electronic circuit was developed for signal generation and post-treatment of each sensor signal. By phase shifting the electrodes supplying the signal, it was possible to establish a rotating electric field sweeping across the test section. The fundamental principle of using a multiple-electrode configuration is based on reducing signal sensitivity to the non-uniform cross-section void fraction distribution problem. Static calibration curves were obtained for both sensors, and dynamic signal analyses for bubbly, slug, and turbulent churn flows were carried out. Flow parameters such as Taylor bubble velocity and length were obtained by using cross-correlation techniques. As an application of the void fraction tested, vertical flow pattern identification could be established by using the probability density function technique for void fractions ranging from 0% to nearly 70%.

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Crushed stone mining is the third largest mining economy in Brazil, where almost half is produced in the Sao Paulo metropolitan region. The segment registers the highest number of accidents among the extractive industries, which justifies the concern with workers` health and safety, and the importance of controlling occupational hazards. Since 2002, the NR-22 Standard (NR-22: Occupational Health and Safety in Mining) makes compulsory the elaboration of a Risk Management Program that identifies risks and establishes control measures. Considering the crushed stone mining industry importance to the state, this paper evaluates and discusses the risks identified in unit operations during the production process of crushed stone in an open pit mine in order to propose control measures for the development of the Risk Management Program. Although this study refers to a specific quarry, it can be applied to other mines from the same sector since some considerations are made regarding differences in manufacturing processes. The research was based on the identification of the main risks associated with drilling, blasting, load & haulage, crushing and screening through field measurements of some hazardous agents, together with company reports. The results contributed to the choice of the appropriate control measures for the improvement Of workers` health and safety conditions.

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The paper discusses the effect of stress triaxiality on the onset and evolution of damage in ductile metals. A series of tests including shear tests and experiments oil smooth and pre-notched tension specimens wits carried Out for it wide range of stress triaxialities. The underlying continuum damage model is based oil kinematic definition of damage tensors. The modular structure of the approach is accomplished by the decomposition of strain rates into elastic, plastic and damage parts. Free energy functions with respect to fictitious undamaged configurations as well as damaged ones are introduced separately leading to elastic material laws which are affected by increasing damage. In addition, a macroscopic yield condition and a flow rule are used to adequately describe the plastic behavior. Numerical simulations of the experiments are performed and good correlation of tests and numerical results is achieved. Based oil experimental and numerical data the damage criterion formulated in stress space is quantified. Different branches of this function are taken into account corresponding to different damage modes depending oil stress triaxiality and Lode parameter. In addition, identification of material parameters is discussed ill detail. (C) 2007 Elsevier Ltd. All rights reserved.

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Dynamic experiments in a nonadiabatic packed bed were carried out to evaluate the response to disturbances in wall temperature and inlet airflow rate and temperature. A two-dimensional, pseudo-homogeneous, axially dispersed plug-flow model was numerically solved and used to interpret the results. The model parameters were fitted in distinct stages: effective radial thermal conductivity (K (r)) and wall heat transfer coefficient (h (w)) were estimated from steady-state data and the characteristic packed bed time constant (tau) from transient data. A new correlation for the K (r) in packed beds of cylindrical particles was proposed. It was experimentally proved that temperature measurements using radially inserted thermocouples and a ring-shaped sensor were not distorted by heat conduction across the thermocouple or by the thermal inertia effect of the temperature sensors.

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The influence of guar and xanthan gum and their combined use on dough proofing rate and its calorimetric properties was investigated. Fusion enthalpy, which is related to the amount of frozen water, was influenced by frozen dough formulation and storage time; specifically gum addition reduced the fusion enthalpy in comparison to control formulation, 76.9 J/g for formulation with both gums and 81.2 J/g for control, at 28th day. Other calorimetric parameters, such as T(g) and freezable water amount, were also influenced by frozen storage time. For all formulations, proofing rate of dough after freezing, frozen storage time and thawing, decreased in comparison to non-frozen dough, indicating that the freezing process itself was more detrimental to the proofing rate than storage time. For all formulations, the mean value of proofing rate was 2.97 +/- 0.24 cm(3) min(-1) per 100 g of non-frozen dough and 2.22 +/- 0.12 cm(3) min(-1) per 100 g of frozen dough. Also the proofing rate of non-frozen dough with xanthan gum decreased significantly in relation to dough without gums and dough with only guar gum. Optical microscopy analyses showed that the gas cell production after frozen storage period was reduced, which is in agreement with the proofing rate results. (C) 2008 Elsevier Ltd. All rights reserved.

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The trapezium is often a better approximation for the FinFET cross-section shape, rather than the design-intended rectangle. The frequent width variations along the vertical direction, caused by the etching process that is used for fin definition, may imply in inclined sidewalls and the inclination angles can vary in a significant range. These geometric variations may cause some important changes in the device electrical characteristics. This work analyzes the influence of the FinFET sidewall inclination angle on some relevant parameters for analog design, such as threshold voltage, output conductance, transconductance, intrinsic voltage gain (A V), gate capacitance and unit-gain frequency, through 3D numeric simulation. The intrinsic gain is affected by alterations in transconductance and output conductance. The results show that both parameters depend on the shape, but in different ways. Transconductance depends mainly on the sidewall inclination angle and the fixed average fin width, whereas the output conductance depends mainly on the average fin width and is weakly dependent on the sidewall inclination angle. The simulation results also show that higher voltage gains are obtained for smaller average fin widths with inclination angles that correspond to inverted trapeziums, i.e. for shapes where the channel width is larger at the top than at the transistor base because of the higher attained transconductance. When the channel top is thinner than the base, the transconductance degradation affects the intrinsic voltage gain. The total gate capacitances also present behavior dependent on the sidewall angle, with higher values for inverted trapezium shapes and, as a consequence, lower unit-gain frequencies.

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The temperature influence on the gate-induced floating body effect (GIFBE) in fully depleted (FD) silicon-on-insulator (SOI) nMOSFETs is investigated, based on experimental results and two-dimensional numerical simulations. The GIFBE behavior will be evaluated taking into account the impact of carrier recombination and of the effective electric field mobility degradation on the second peak in the transconductance (gm). This floating body effect is also analyzed as a function of temperature. It is shown that the variation of the studied parameters with temperature results in a ""C"" shape of the threshold voltage corresponding with the second peak in the gm curve. (C) 2008 Elsevier Ltd. All rights reserved.

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In this paper, we devise a separation principle for the finite horizon quadratic optimal control problem of continuous-time Markovian jump linear systems driven by a Wiener process and with partial observations. We assume that the output variable and the jump parameters are available to the controller. It is desired to design a dynamic Markovian jump controller such that the closed loop system minimizes the quadratic functional cost of the system over a finite horizon period of time. As in the case with no jumps, we show that an optimal controller can be obtained from two coupled Riccati differential equations, one associated to the optimal control problem when the state variable is available, and the other one associated to the optimal filtering problem. This is a separation principle for the finite horizon quadratic optimal control problem for continuous-time Markovian jump linear systems. For the case in which the matrices are all time-invariant we analyze the asymptotic behavior of the solution of the derived interconnected Riccati differential equations to the solution of the associated set of coupled algebraic Riccati equations as well as the mean square stabilizing property of this limiting solution. When there is only one mode of operation our results coincide with the traditional ones for the LQG control of continuous-time linear systems.

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Functional magnetic resonance imaging (fMRI) has become an important tool in Neuroscience due to its noninvasive and high spatial resolution properties compared to other methods like PET or EEG. Characterization of the neural connectivity has been the aim of several cognitive researches, as the interactions among cortical areas lie at the heart of many brain dysfunctions and mental disorders. Several methods like correlation analysis, structural equation modeling, and dynamic causal models have been proposed to quantify connectivity strength. An important concept related to connectivity modeling is Granger causality, which is one of the most popular definitions for the measure of directional dependence between time series. In this article, we propose the application of the partial directed coherence (PDC) for the connectivity analysis of multisubject fMRI data using multivariate bootstrap. PDC is a frequency domain counterpart of Granger causality and has become a very prominent tool in EEG studies. The achieved frequency decomposition of connectivity is useful in separating interactions from neural modules from those originating in scanner noise, breath, and heart beating. Real fMRI dataset of six subjects executing a language processing protocol was used for the analysis of connectivity. Hum Brain Mapp 30:452-461, 2009. (C) 2007 Wiley-Liss, Inc.

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Distribution of timing signals is an essential factor for the development of digital systems for telecommunication networks, integrated circuits and manufacturing automation. Originally, this distribution was implemented by using the master-slave architecture with a precise master clock generator sending signals to phase-locked loops (PLL) working as slave oscillators. Nowadays, wireless networks with dynamical connectivity and the increase in size and operation frequency of the integrated circuits suggest that the distribution of clock signals could be more efficient if mutually connected architectures were used. Here, mutually connected PLL networks are studied and conditions for synchronous states existence are analytically derived, depending on individual node parameters and network connectivity, considering that the nodes are nonlinear oscillators with nonlinear coupling conditions. An expression for the network synchronisation frequency is obtained. The lock-in range and the transmission error bounds are analysed providing hints to the design of this kind of clock distribution system.

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This work deals with a procedure for model re-identification of a process in closed loop with ail already existing commercial MPC. The controller considered here has a two-layer structure where the upper layer performs a target calculation based on a simplified steady-state optimization of the process. Here, it is proposed a methodology where a test signal is introduced in a tuning parameter of the target calculation layer. When the outputs are controlled by zones instead of at fixed set points, the approach allows the continuous operation of the process without an excessive disruption of the operating objectives as process constraints and product specifications remain satisfied during the identification test. The application of the method is illustrated through the simulation of two processes of the oil refining industry. (c) 2008 Elsevier Ltd. All rights reserved.

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In this paper, we deal with a generalized multi-period mean-variance portfolio selection problem with market parameters Subject to Markov random regime switchings. Problems of this kind have been recently considered in the literature for control over bankruptcy, for cases in which there are no jumps in market parameters (see [Zhu, S. S., Li, D., & Wang, S. Y. (2004). Risk control over bankruptcy in dynamic portfolio selection: A generalized mean variance formulation. IEEE Transactions on Automatic Control, 49, 447-457]). We present necessary and Sufficient conditions for obtaining an optimal control policy for this Markovian generalized multi-period meal-variance problem, based on a set of interconnected Riccati difference equations, and oil a set of other recursive equations. Some closed formulas are also derived for two special cases, extending some previous results in the literature. We apply the results to a numerical example with real data for Fisk control over bankruptcy Ill a dynamic portfolio selection problem with Markov jumps selection problem. (C) 2008 Elsevier Ltd. All rights reserved.

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A prenylated benzophenone, hyperibone A, was isolated from the hexane fraction of Brazilian propolis type 6. Its structure was determined by spectral analysis including 2D NMR. This compound exhibited cytotoxic activity against HeLa tumor cells (IC(50) = 0.1756 mu M), strong antimicrobial activity (MIC range-0.73-6.6 mu g/mL; MBC range-2.92-106 mu g/mL) against Streptococcus mutans, Streptococcus sobrinus, Streptococcus oralis, Staphylococcus aureus, and Actinomyces naeslundii, and the results of its cytotoxic and antimicrobial activities were considered good. (C) 2009 Elsevier Ltd. All rights reserved.

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An important topic in genomic sequence analysis is the identification of protein coding regions. In this context, several coding DNA model-independent methods based on the occurrence of specific patterns of nucleotides at coding regions have been proposed. Nonetheless, these methods have not been completely suitable due to their dependence on an empirically predefined window length required for a local analysis of a DNA region. We introduce a method based on a modified Gabor-wavelet transform (MGWT) for the identification of protein coding regions. This novel transform is tuned to analyze periodic signal components and presents the advantage of being independent of the window length. We compared the performance of the MGWT with other methods by using eukaryote data sets. The results show that MGWT outperforms all assessed model-independent methods with respect to identification accuracy. These results indicate that the source of at least part of the identification errors produced by the previous methods is the fixed working scale. The new method not only avoids this source of errors but also makes a tool available for detailed exploration of the nucleotide occurrence.

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The application of airborne laser scanning (ALS) technologies in forest inventories has shown great potential to improve the efficiency of forest planning activities. Precise estimates, fast assessment and relatively low complexity can explain the good results in terms of efficiency. The evolution of GPS and inertial measurement technologies, as well as the observed lower assessment costs when these technologies are applied to large scale studies, can explain the increasing dissemination of ALS technologies. The observed good quality of results can be expressed by estimates of volumes and basal area with estimated error below the level of 8.4%, depending on the size of sampled area, the quantity of laser pulses per square meter and the number of control plots. This paper analyzes the potential of an ALS assessment to produce certain forest inventory statistics in plantations of cloned Eucalyptus spp with precision equal of superior to conventional methods. The statistics of interest in this case were: volume, basal area, mean height and dominant trees mean height. The ALS flight for data assessment covered two strips of approximately 2 by 20 Km, in which clouds of points were sampled in circular plots with a radius of 13 m. Plots were sampled in different parts of the strips to cover different stand ages. The clouds of points generated by the ALS assessment: overall height mean, standard error, five percentiles (height under which we can find 10%, 30%, 50%,70% and 90% of the ALS points above ground level in the cloud), and density of points above ground level in each percentile were calculated. The ALS statistics were used in regression models to estimate mean diameter, mean height, mean height of dominant trees, basal area and volume. Conventional forest inventory sample plots provided real data. For volume, an exploratory assessment involving different combinations of ALS statistics allowed for the definition of the most promising relationships and fitting tests based on well known forest biometric models. The models based on ALS statistics that produced the best results involved: the 30% percentile to estimate mean diameter (R(2)=0,88 and MQE%=0,0004); the 10% and 90% percentiles to estimate mean height (R(2)=0,94 and MQE%=0,0003); the 90% percentile to estimate dominant height (R(2)=0,96 and MQE%=0,0003); the 10% percentile and mean height of ALS points to estimate basal area (R(2)=0,92 and MQE%=0,0016); and, to estimate volume, age and the 30% and 90% percentiles (R(2)=0,95 MQE%=0,002). Among the tested forest biometric models, the best fits were provided by the modified Schumacher using age and the 90% percentile, modified Clutter using age, mean height of ALS points and the 70% percentile, and modified Buckman using age, mean height of ALS points and the 10% percentile.