Estimation of hexenuronic acids and kappa number in kraft pulps of Eucalyptus globulus by Fourier transform near infrared spectroscopy and multivariate analysis

Fourier transform near infrared (FT-NIR) spectroscopy was evaluated as an analytical too[ for monitoring residual Lignin, kappa number and hexenuronic acids (HexA) content in kraft pulps of Eucalyptus globulus. Sets of pulp samples were prepared under different cooking conditions to obtain a wide range of compound concentrations that were characterised by conventional wet chemistry analytical methods. The sample group was also analysed using FT-NIR spectroscopy in order to establish prediction models for the pulp characteristics. Several models were applied to correlate chemical composition in samples with the NIR spectral data by means of PCR or PLS algorithms. Calibration curves were built by using all the spectral data or selected regions. Best calibration models for the quantification of lignin, kappa and HexA were proposed presenting R-2 values of 0.99. Calibration models were used to predict pulp titers of 20 external samples in a validation set. The lignin concentration and kappa number in the range of 1.4-18% and 8-62, respectively, were predicted fairly accurately (standard error of prediction, SEP 1.1% for lignin and 2.9 for kappa). The HexA concentration (range of 5-71 mmol kg(-1) pulp) was more difficult to predict and the SEP was 7.0 mmol kg(-1) pulp in a model of HexA quantified by an ultraviolet (UV) technique and 6.1 mmol kg(-1) pulp in a model of HexA quantified by anion-exchange chromatography (AEC). Even in wet chemical procedures used for HexA determination, there is no good agreement between methods as demonstrated by the UV and AEC methods described in the present work. NIR spectroscopy did provide a rapid estimate of HexA content in kraft pulps prepared in routine cooking experiments.

Noise reduction in biomedical speech signal processing based on time and frequency Kalman filtering combined with spectral subtraction

The goal of this paper is to study and propose a new technique for noise reduction used during the reconstruction of speech signals, particularly for biomedical applications. The proposed method is based on Kalman filtering in the time domain combined with spectral subtraction. Comparison with discrete Kalman filter in the frequency domain shows better performance of the proposed technique. The performance is evaluated by using the segmental signal-to-noise ratio and the Itakura-Saito`s distance. Results have shown that Kalman`s filter in time combined with spectral subtraction is more robust and efficient, improving the Itakura-Saito`s distance by up to four times. (C) 2007 Elsevier Ltd. All rights reserved.

An approach based on neural networks for estimation and generalization of crossflow filtration processes

The crossflow filtration process differs of the conventional filtration by presenting the circulation flow tangentially to the filtration surface. The conventional mathematical models used to represent the process have some limitations in relation to the identification and generalization of the system behaviour. In this paper, a system based on artificial neural networks is developed to overcome the problems usually found in the conventional mathematical models. More specifically, the developed system uses an artificial neural network that simulates the behaviour of the crossflow filtration process in a robust way. Imprecisions and uncertainties associated with the measurements made on the system are automatically incorporated in the neural approach. Simulation results are presented to justify the validity of the proposed approach. (C) 2007 Elsevier B.V. All rights reserved.

Innovation concept for measurement gross error detection and identification in power system state estimation

In this study, the innovation approach is used to estimate the measurement total error associated with power system state estimation. This is required because the power system equations are very much correlated with each other and as a consequence part of the measurements errors is masked. For that purpose an index, innovation index (II), which provides the quantity of new information a measurement contains is proposed. A critical measurement is the limit case of a measurement with low II, it has a zero II index and its error is totally masked. In other words, that measurement does not bring any innovation for the gross error test. Using the II of a measurement, the masked gross error by the state estimation is recovered; then the total gross error of that measurement is composed. Instead of the classical normalised measurement residual amplitude, the corresponding normalised composed measurement residual amplitude is used in the gross error detection and identification test, but with m degrees of freedom. The gross error processing turns out to be very simple to implement, requiring only few adaptations to the existing state estimation software. The IEEE-14 bus system is used to validate the proposed gross error detection and identification test.

Effect of impeller type and stirring frequency on the behavior of an AnSBBR in the treatment of low-strength wastewater

The influence of impeller type and stirring frequency on the performance of a mechanically stirred anaerobic sequencing batch reactor containing immobilized biomass on an inert support (AnSBBR - Anaerobic Sequencing Batch Biofilm Reactor) was evaluated. The biomass was immobilized on polyurethane foam cubes placed in a stainless-steel basket inside a glass cylinder. Each 8-h batch run consisted of three stages: feed (10 min), reaction (460 min) and discharge (10 min) at 30 degrees C. Experiments were performed with four impeller types, i.e., helical, flat-blade, inclined-blade and curved-blade turbines, at stirring frequencies ranging from 100 to 1100 rpm. Synthetic wastewater was used in all experiments with an organic-matter concentration of 530 +/- 37 mg/L measured as chemical oxygen demand (COD). The reactor achieved an organic-matter removal efficiency of around 87% under all investigated conditions. Analysis of the four impeller types and the investigated stirring frequencies showed that mass transfer in the liquid phase was affected not only by the applied stirring frequency but also by the agitation mode imposed by each impeller type. The best reactor performance at all stirring frequencies was obtained when agitation was provided by the flat-blade turbine impeller. (C) 2010 Elsevier Ltd. All rights reserved.

Estimation of Mass Transfer Velocity Based on Measured Turbulence Parameters

The aim of this study is to quantify the mass transfer velocity using turbulence parameters from simultaneous measurements of oxygen concentration fields and velocity fields. The surface divergence model was considered in more detail, using data obtained for the lower range of beta (surface divergence). It is shown that the existing models that use the divergence concept furnish good predictions for the transfer velocity also for low values of beta, in the range of this study. Additionally, traditional conceptual models, such as the film model, the penetration-renewal model, and the large eddy model, were tested using the simultaneous information of concentration and velocity fields. It is shown that the film and the surface divergence models predicted the mass transfer velocity for all the range of the equipment Reynolds number used here. The velocity measurements showed viscosity effects close to the surface, which indicates that the surface was contaminated with some surfactant. Considering the results, this contamination can be considered slight for the mass transfer predictions. (C) 2009 American Institute of Chemical Engineers AIChE J, 56: 2005-2017; 2010

Distribution systems fault analysis considering fault resistance estimation

Fault resistance is a critical component of electric power systems operation due to its stochastic nature. If not considered, this parameter may interfere in fault analysis studies. This paper presents an iterative fault analysis algorithm for unbalanced three-phase distribution systems that considers a fault resistance estimate. The proposed algorithm is composed by two sub-routines, namely the fault resistance and the bus impedance. The fault resistance sub-routine, based on local fault records, estimates the fault resistance. The bus impedance sub-routine, based on the previously estimated fault resistance, estimates the system voltages and currents. Numeric simulations on the IEEE 37-bus distribution system demonstrate the algorithm`s robustness and potential for offline applications, providing additional fault information to Distribution Operation Centers and enhancing the system restoration process. (C) 2011 Elsevier Ltd. All rights reserved.

Recursive linear estimation for general discrete-time descriptor systems

This paper considers the optimal linear estimates recursion problem for discrete-time linear systems in its more general formulation. The system is allowed to be in descriptor form, rectangular, time-variant, and with the dynamical and measurement noises correlated. We propose a new expression for the filter recursive equations which presents an interesting simple and symmetric structure. Convergence of the associated Riccati recursion and stability properties of the steady-state filter are provided. (C) 2010 Elsevier Ltd. All rights reserved.

A Power-Quality Index to Assess the Impact of Voltage Harmonic Distortions and Unbalance to Three-Phase Induction Motors

This paper discusses the need to simultaneously monitor voltage unbalance and harmonic distortions in addition to root-mean-square voltage values. An alternative way to obtain the parameters related to voltage unbalance at fundamental frequency as well as voltage harmonic distortions is here proposed, which is based on the representation of instantaneous values at the axes and at the instantaneous Euclidean norm. A new power-quality (PQ) index is then proposed to combine the effects of voltage unbalance and harmonic distortions. This new index is easily implemented into existing electronic power meters. This PQ index is determined from the analysis of temperature rise in induction motor windings, which were tested for long periods of time. This paper also shows that these voltage disturbances, which are harmful to the lifetime expectancy of motors, can be measured by alternative ways in relation to conventional methods. Although this paper deals with induction motors only, the results show the relevance for further studies on other pieces of equipment.

Estimating wave spectra from the motions of moored vessels: Experimental validation

The practicability of estimating directional wave spectra based on a vessel`s 1st order response has been recently addressed by several researchers. Different alternatives regarding statistical inference methods and possible drawbacks that could arise from their application have been extensively discussed, with an apparent preference for estimations based on Bayesian inference algorithms. Most of the results on this matter, however, rely exclusively on numerical simulations or at best on few and sparse full-scale measurements, comprising a questionable basis for validation purposes. This paper discusses several issues that have recently been debated regarding the advantages of Bayesian inference and different alternatives for its implementation. Among those are the definition of the best set of input motions, the number of parameters required for guaranteeing smoothness of the spectrum in frequency and direction and how to determine their optimum values. These subjects are addressed in the light of an extensive experimental campaign performed with a small-scale model of an FPSO platform (VLCC hull), which was conducted in an ocean basin in Brazil. Tests involved long and short crested seas with variable levels of directional spreading and also bimodal conditions. The calibration spectra measured in the tank by means of an array of wave probes configured the paradigm for estimations. Results showed that a wide range of sea conditions could be estimated with good precision, even those with somewhat low peak periods. Some possible drawbacks that have been pointed out in previous works concerning the viability of employing large vessels for such a task are then refuted. Also, it is shown that a second parameter for smoothing the spectrum in frequency may indeed increase the accuracy in some situations, although the criterion usually proposed for estimating the optimum values (ABIC) demands large computational effort and does not seem adequate for practical on-board systems, which require expeditious estimations. (C) 2009 Elsevier Ltd. All rights reserved.

Effects of weld strength mismatch on J and CTOD estimation procedure for SE(B) specimens

This work examines the effect of weld strength mismatch on fracture toughness measurements defined by J and CTOD fracture parameters using single edge notch bend (SE(B)) specimens. A central objective of the present study is to enlarge on previous developments of J and CTOD estimation procedures for welded bend specimens based upon plastic eta factors (eta) and plastic rotational factors (r (p) ). Very detailed non-linear finite element analyses for plane-strain models of standard SE(B) fracture specimens with a notch located at the center of square groove welds and in the heat affected zone provide the evolution of load with increased crack mouth opening displacement required for the estimation procedure. One key result emerging from the analyses is that levels of weld strength mismatch within the range +/- 20% mismatch do not affect significantly J and CTOD estimation expressions applicable to homogeneous materials, particularly for deeply cracked fracture specimens with relatively large weld grooves. The present study provides additional understanding on the effect of weld strength mismatch on J and CTOD toughness measurements while, at the same time, adding a fairly extensive body of results to determine parameters J and CTOD for different materials using bend specimens with varying geometries and mismatch levels.

Directional Wave Spectrum Estimation Based on Vessel`s 1st-order Motions: Field Results

In this paper, 2 different approaches for estimating the directional wave spectrum based on a vessel`s 1st-order motions are discussed, and their predictions are compared to those provided by a wave buoy. The real-scale data were obtained in an extensive monitoring campaign based on an FPSO unit operating at Campos Basin, Brazil. Data included vessel motions, heading and tank loadings. Wave field information was obtained by means of a heave-pitch-roll buoy installed in the vicinity of the unit. `two of the methods most widely used for this kind of analysis are considered, one based on Bayesian statistical inference, the other consisting of a parametrical representation of the wave spectrum. The performance of both methods is compared, and their sensitivity to input parameters is discussed. This analysis complements a set of previous validations based on numerical and towing-tank results and allows for a preliminary evaluation of reliability when applying the methodology at full scale.

Low-frequency noise and static analysis of the impact of the TiN metal gate thicknesses on n- and p-channel MuGFETs

The impact of the titanium nitride (TIN) gate electrode thickness has been investigated in n and p channel SOI multiple gate field effect transistors (MuGFETs) through low frequency noise charge pumping and static measurements as well as capacitance-voltage curves The results suggest that a thicker TIN metal gate electrode gives rise to a higher EOT a lower mobility and a higher interface trap density The devices have also been studied for different back gate biases where the GIFBE onset occurs at lower front-gate voltage for thinner TIN metal gate thickness and at higher V(GF) In addition it is demonstrated that post deposition nitridation of the MOCVD HfSiO gate dielectric exhibits an unexpected trend with TIN gate electrode thickness where a continuous variation of EOT and an increase on the degradation of the interface quality are observed (C) 2010 Elsevier Ltd All rights reserved

Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm

We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton`s method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of least-mean-square (LMS) type distributed adaptive filters with colored inputs. The analysis of transient and steady-state performances at each individual node within the network is developed by using a weighted spatial-temporal energy conservation relation and confirmed by computer simulations. The simulation results also verify that the proposed algorithm provides not only a faster convergence rate but also an improved steady-state performance as compared to an LMS-based scheme. In addition, the new approach attains an acceptable misadjustment performance with lower computational and memory cost, provided the number of regressor vectors and filter length parameters are appropriately chosen, as compared to a distributed recursive-least-squares (RLS) based method.

Information theoretic interpretation of frequency domain connectivity measures

In order to provide adequate multivariate measures of information flow between neural structures, modified expressions of partial directed coherence (PDC) and directed transfer function (DTF), two popular multivariate connectivity measures employed in neuroscience, are introduced and their formal relationship to mutual information rates are proved.