The shallow water approximation applied to the aluminium electrolysis process

The industrial production of aluminium is an electrolysis process where two superposed horizontal liquid layers are subjected to a mainly vertical electric current supplied by carbon electrodes. The lower layer consists of molten aluminium and lies on the cathode. The upper layer is the electrolyte and is covered by the anode. The interface between the two layers is often perturbed, leading to oscillations, or waves, similar to the waves on the surface of seas or lakes. The presence of electric currents and the resulting magnetic field are responsible for electromagnetic (Lorentz) forces within the fluid, which can amplify these oscillations and have an adverse influence on the process. The electrolytic bath vertical to horizontal aspect ratio is such, that it is advantageous to use the shallow water equations to model the interface motion. These are the depth-averaging the Navier-Stokes equations so that nonlinear and dispersion terms may be taken into account. Although these terms are essential to the prediction of wave dynamics, they are neglected in most of the literature on interface instabilities in aluminium reduction cells where only the linear theory is usually considered. The unknown variables are the two horizontal components of the fluid velocity, the height of the interface and the electric potential. In this application, a finite volume resolution of the double-layer shallow water equations including the electromagnetic sources has been developed, for incorporation into a generic three-dimensional computational fluid dynamics code that also deals with heat transfer within the cell.

Random path sampling applied to vector models of magnetism

The recently reported Monte Carlo Random Path Sampling method (RPS) is here improved and its application is expanded to the study of the 2D and 3D Ising and discrete Heisenberg models. The methodology was implemented to allow use in both CPU-based high-performance computing infrastructures (C/MPI) and GPU-based (CUDA) parallel computation, with significant computational performance gains. Convergence is discussed, both in terms of free energy and magnetization dependence on field/temperature. From the calculated magnetization-energy joint density of states, fast calculations of field and temperature dependent thermodynamic properties are performed, including the effects of anisotropy on coercivity, and the magnetocaloric effect. The emergence of first-order magneto-volume transitions in the compressible Ising model is interpreted using the Landau theory of phase transitions. Using metallic Gadolinium as a real-world example, the possibility of using RPS as a tool for computational magnetic materials design is discussed. Experimental magnetic and structural properties of a Gadolinium single crystal are compared to RPS-based calculations using microscopic parameters obtained from Density Functional Theory.

Hierarchically grouped 2D local features applied to edge contour localisation

One of the most significant research topics in computer vision is object detection. Most of the reported object detection results localise the detected object within a bounding box, but do not explicitly label the edge contours of the object. Since object contours provide a fundamental diagnostic of object shape, some researchers have initiated work on linear contour feature representations for object detection and localisation. However, linear contour feature-based localisation is highly dependent on the performance of linear contour detection within natural images, and this can be perturbed significantly by a cluttered background. In addition, the conventional approach to achieving rotation-invariant features is to rotate the feature receptive field to align with the local dominant orientation before computing the feature representation. Grid resampling after rotation adds extra computational cost and increases the total time consumption for computing the feature descriptor. Though it is not an expensive process if using current computers, it is appreciated that if each step of the implementation is faster to compute especially when the number of local features is increasing and the application is implemented on resource limited ”smart devices”, such as mobile phones, in real-time. Motivated by the above issues, a 2D object localisation system is proposed in this thesis that matches features of edge contour points, which is an alternative method that takes advantage of the shape information for object localisation. This is inspired by edge contour points comprising the basic components of shape contours. In addition, edge point detection is usually simpler to achieve than linear edge contour detection. Therefore, the proposed localization system could avoid the need for linear contour detection and reduce the pathological disruption from the image background. Moreover, since natural images usually comprise many more edge contour points than interest points (i.e. corner points), we also propose new methods to generate rotation-invariant local feature descriptors without pre-rotating the feature receptive field to improve the computational efficiency of the whole system. In detail, the 2D object localisation system is achieved by matching edge contour points features in a constrained search area based on the initial pose-estimate produced by a prior object detection process. The local feature descriptor obtains rotation invariance by making use of rotational symmetry of the hexagonal structure. Therefore, a set of local feature descriptors is proposed based on the hierarchically hexagonal grouping structure. Ultimately, the 2D object localisation system achieves a very promising performance based on matching the proposed features of edge contour points with the mean correct labelling rate of the edge contour points 0.8654 and the mean false labelling rate 0.0314 applied on the data from Amsterdam Library of Object Images (ALOI). Furthermore, the proposed descriptors are evaluated by comparing to the state-of-the-art descriptors and achieve competitive performances in terms of pose estimate with around half-pixel pose error.

Variational ensemble Kalman filtering applied to data assimilation problems in computational fluid dynamics

One challenge on data assimilation (DA) methods is how the error covariance for the model state is computed. Ensemble methods have been proposed for producing error covariance estimates, as error is propagated in time using the non-linear model. Variational methods, on the other hand, use the concepts of control theory, whereby the state estimate is optimized from both the background and the measurements. Numerical optimization schemes are applied which solve the problem of memory storage and huge matrix inversion needed by classical Kalman filter methods. Variational Ensemble Kalman filter (VEnKF), as a method inspired the Variational Kalman Filter (VKF), enjoys the benefits from both ensemble methods and variational methods. It avoids filter inbreeding problems which emerge when the ensemble spread underestimates the true error covariance. In VEnKF this is tackled by resampling the ensemble every time measurements are available. One advantage of VEnKF over VKF is that it needs neither tangent linear code nor adjoint code. In this thesis, VEnKF has been applied to a two-dimensional shallow water model simulating a dam-break experiment. The model is a public code with water height measurements recorded in seven stations along the 21:2 m long 1:4 m wide flume’s mid-line. Because the data were too sparse to assimilate the 30 171 model state vector, we chose to interpolate the data both in time and in space. The results of the assimilation were compared with that of a pure simulation. We have found that the results revealed by the VEnKF were more realistic, without numerical artifacts present in the pure simulation. Creating a wrapper code for a model and DA scheme might be challenging, especially when the two were designed independently or are poorly documented. In this thesis we have presented a non-intrusive approach of coupling the model and a DA scheme. An external program is used to send and receive information between the model and DA procedure using files. The advantage of this method is that the model code changes needed are minimal, only a few lines which facilitate input and output. Apart from being simple to coupling, the approach can be employed even if the two were written in different programming languages, because the communication is not through code. The non-intrusive approach is made to accommodate parallel computing by just telling the control program to wait until all the processes have ended before the DA procedure is invoked. It is worth mentioning the overhead increase caused by the approach, as at every assimilation cycle both the model and the DA procedure have to be initialized. Nonetheless, the method can be an ideal approach for a benchmark platform in testing DA methods. The non-intrusive VEnKF has been applied to a multi-purpose hydrodynamic model COHERENS to assimilate Total Suspended Matter (TSM) in lake Säkylän Pyhäjärvi. The lake has an area of 154 km2 with an average depth of 5:4 m. Turbidity and chlorophyll-a concentrations from MERIS satellite images for 7 days between May 16 and July 6 2009 were available. The effect of the organic matter has been computationally eliminated to obtain TSM data. Because of computational demands from both COHERENS and VEnKF, we have chosen to use 1 km grid resolution. The results of the VEnKF have been compared with the measurements recorded at an automatic station located at the North-Western part of the lake. However, due to TSM data sparsity in both time and space, it could not be well matched. The use of multiple automatic stations with real time data is important to elude the time sparsity problem. With DA, this will help in better understanding the environmental hazard variables for instance. We have found that using a very high ensemble size does not necessarily improve the results, because there is a limit whereby additional ensemble members add very little to the performance. Successful implementation of the non-intrusive VEnKF and the ensemble size limit for performance leads to an emerging area of Reduced Order Modeling (ROM). To save computational resources, running full-blown model in ROM is avoided. When the ROM is applied with the non-intrusive DA approach, it might result in a cheaper algorithm that will relax computation challenges existing in the field of modelling and DA.

Development of procedures for the triazole fungicides determination in fruits and liquid samples using microextraction techniques and chromatographic separation

Agricultural crops can be damaged by funguses, insects, worms and other organisms that cause diseases and decrease the yield of production. The effect of these damaging agents can be reduced using pesticides. Among them, triazole compounds are effective substances against fungus; for example, Oidium. Nevertheless, it has been detected that the residues of these fungicides in foods as well as in derivate products can affect the health of the consumers. Therefore, the European Union has established several regulations fixing the maximum residue of pesticide levels in a wide range of foods trying to assure the consumer safety. Hence, it is very important to develop adequate methods to determine these pesticide compounds. In most cases, gas or liquid chromatographic (GC, LC) separations are used in the analysis of the samples. But firstly, it is necessary to use proper sample treatments in order to preconcentrate and isolate the target analytes. To reach this aim, microextraction techniques are very effective tools; because allow to do both preconcentration and extraction of the analytes in one simple step that considerably reduces the source of errors. With these objectives, two remarkable techniques have been widely used during the last years: solid phase microextraction (SPME) and liquid phase microextraction (LPME) with its different options. Both techniques that avoid the use or reduce the amount of toxic solvents are convenient coupled to chromatographic equipments providing good quantitative results in a wide number of matrices and compounds. In this work simple and reliable methods have been developed using SPME and ultrasound assisted emulsification microextraction (USAEME) coupled to GC or LC for triazole fungicides determination. The proposed methods allow confidently determine triazole concentrations of μg L‐1 order in different fruit samples. Chemometric tools have been used to accomplish successful determinations. Firstly, in the selection and optimization of the variables involved in the microextraction processes; and secondly, to overcome the problems related to the overlapping peaks. Different fractional factorial designs have been used for the screening of the experimental variables; and central composite designs have been carried out to get the best experimental conditions. Trying to solve the overlapping peak problems multivariate calibration methods have been used. Parallel Factor Analysis 2 (PARAFAC2), Multivariate Curve Resolution (MCR) and Parallel Factor Analysis with Linear Dependencies (PARALIND) have been proposed, the adequate algorithms have been used according to data characteristics, and the results have been compared. Because its occurrence in Basque Country and its relevance in the production of cider and txakoli regional wines the grape and apple samples were selected. These crops are often treated with triazole compounds trying to solve the problems caused by the funguses. The peel and pulp from grape and apple, their juices and some commercial products such as musts, juice and cider have been analysed showing the adequacy of the developed methods for the triazole determination in this kind of fruit samples.

Geoprocessing applied to the assessment of environmental noise: a case study in the city of Sorocaba, São Paulo, Brazil

Noise mapping has been used as an instrument for assessment of environmental noise, helping to support decision making on urban planning. In Brazil, urban noise is not yet recognized as a major environmental problem by the government. Besides, cities that have databases to drive acoustic simulations, making use of advanced noise mapping systems, are rare. This study sought an alternative method of noise mapping through the use of geoprocessing, which is feasible for the Brazilian reality and for other developing countries. The area chosen for the study was the central zone of the city of Sorocaba, located in So Paulo State, Brazil. The proposed method was effective in the spatial evaluation of equivalent sound pressure level. The results showed an urban area with high noise levels that exceed the legal standard, posing a threat to the welfare of the population.

An investigation into the suitability of time-of-flight mass spectrometry in forensic toxicology

Liquid chromatography coupled with mass spectrometry is one of the most powerful tools in the toxicologist’s arsenal to detect a wide variety of compounds from many different matrices. However, the huge number of potentially abused substances and new substances especially designed as intoxicants poses a problem in a forensic toxicology setting. Most methods are targeted and designed to cover a very specific drug or group of drugs while many other substances remain undetected. High resolution mass spectrometry, more specifically time-of-flight mass spectrometry, represents an extremely powerful tool in analysing a multitude of compounds not only simultaneously but also retroactively. The data obtained through the time-of-flight instrument contains all compounds made available from sample extraction and chromatography, which can be processed at a later time with an improved library to detect previously unrecognised compounds without having to analyse the respective sample again. The aim of this project was to determine the utility and limitations of time-of-flight mass spectrometry as a general and easily expandable screening method. The resolution of time-of-flight mass spectrometry allows for the separation of compounds with the same nominal mass but distinct exact masses without the need to separate them chromatographically. To simulate the wide variety of potentially encountered drugs in such a general screening method, seven drugs (morphine, cocaine, zolpidem, diazepam, amphetamine, MDEA and THC) were chosen to represent this variety in terms of mass, properties and functional groups. Consequently, several liquid-liquid and solid phase extractions were applied to urine samples to determine the most general suitable and unspecific extraction. Chromatography was optimised by investigating the parameters pH, concentration, organic solvent and gradient of the mobile phase to improve data obtained by the time-of-flight instrument. The resulting method was validated as a qualitative confirmation/identification method. Data processing was automated using the software TargetAnalysis, which provides excellent analyte recognition according to retention time, exact mass and isotope pattern. The recognition of isotope patterns allows excellent recognition of analytes even in interference rich mass spectra and proved to be a good positive indicator. Finally, the validated method was applied to samples received from the A& E Department of Glasgow Royal Infirmary in suspected drug abuse cases and samples received from the Scottish Prison Service, which we received from their own prevalence study targeting drugs of abuse in the prison population. The obtained data was processed with a library established in the course of this work.

IDeS methodology applied to automotive component re-engineering focused on lightweight and high-strength by additive manufacturing

The project aims to gather an understanding of additive manufacturing and other manufacturing 4.0 techniques with an eyesight for industrialization. First the internal material anisotropy of elements created with the most economically feasible FEM technique was established. An understanding of the main drivers for variability for AM was portrayed, with the focus on achieving material internal isotropy. Subsequently, a technique for deposition parameter optimization was presented, further procedure testing was performed following other polymeric materials and composites. A replicability assessment by means of the use of technology 4.0 was proposed, and subsequent industry findings gathered the ultimate need of developing a process that demonstrate how to re-engineer designs in order to show the best results with AM processing. The latest study aims to apply the Industrial Design and Structure Method (IDES) and applying all the knowledge previously stacked into fully reengineer a product with focus of applying tools from 4.0 era, from product feasibility studies, until CAE – FEM analysis and CAM – DfAM. These results would help in making AM and FDM processes a viable option to be combined with composites technologies to achieve a reliable, cost-effective manufacturing method that could also be used for mass market, industry applications.

Detection Of Explosives On The Surface Of Banknotes By Raman Hyperspectral Imaging And Independent Component Analysis.

The aim of this study was to develop a methodology using Raman hyperspectral imaging and chemometric methods for identification of pre- and post-blast explosive residues on banknote surfaces. The explosives studied were of military, commercial and propellant uses. After the acquisition of the hyperspectral imaging, independent component analysis (ICA) was applied to extract the pure spectra and the distribution of the corresponding image constituents. The performance of the methodology was evaluated by the explained variance and the lack of fit of the models, by comparing the ICA recovered spectra with the reference spectra using correlation coefficients and by the presence of rotational ambiguity in the ICA solutions. The methodology was applied to forensic samples to solve an automated teller machine explosion case. Independent component analysis proved to be a suitable method of resolving curves, achieving equivalent performance with the multivariate curve resolution with alternating least squares (MCR-ALS) method. At low concentrations, MCR-ALS presents some limitations, as it did not provide the correct solution. The detection limit of the methodology presented in this study was 50μgcm(-2).

The Biopsychosocial Spiritual Model Applied To The Treatment Of women With Breast Cancer, Through Rime Intervention (relaxation, mental Images, Spirituality).

This postdoctoral study on the application of the RIME intervention in women that had undergone mastectomy and were in treatment, aimed to promote psychospiritual and social transformations to improve the quality of life, self-esteem and hope. A total of 28 women participated and were randomized into two groups. Brief Psychotherapy (PB) (average of six sessions) was administered in the Control Group, and RIME (three sessions) and BP (average of five sessions) were applied in the RIME Group. The quantitative results indicated a significant improvement (38.3%) in the Perception of Quality of Life after RIME according to the WHOQOL, compared both to the BP of the Control Group (12.5%), and the BP of the RIME Group (16.2%). There was a significant improvement in Self-esteem (Rosenberg) after RIME (14.6%) compared to the BP of the Control Group (worsened 35.9%), and the BP of the RIME Group (8.3%). The improvement in well-being, considering the focus worked on (Visual Analog Scale), was significant in the RIME Group (bad to good), as well as in the Control Group (unpleasant to good). The qualitative results indicated that RIME promotes creative transformations in the intrapsychic and interpersonal dimensions, so that new meanings and/or new attitudes emerge into the consciousness. It was observed that RIME has more strength of psychic structure, ego strengthening and provides a faster transformation that BP, therefore it can be indicated for crisis treatment in the hospital environment.

Nanoparticles Applied To Plant Science: A Review.

The present review addresses certain important aspects regarding nanoparticles and the environment, with an emphasis on plant science. The production and characterization of nanoparticles is the focus of this review, providing an idea of the range and the consolidation of these aspects in the literature, with modifications on the routes of synthesis and the application of the analytical techniques for characterization of the nanoparticles (NPs). Additionally, aspects related to the interaction between the NPs and plants, their toxicities, and the phytoremediation process, among others, are also discussed. Future trends are also presented, supplying evidence for certain possibilities regarding new research involving nanoparticles and plants.

Estratégias para individualização de resultados em testes de desempenho

Universidade Estadual de Campinas. Faculdade de Educação Física

Rare earth element and yttrium geochemistry applied to the genetic study of cryolite ore at the Pitinga Mine (Amazon, Brazil)

This work aims at the geochemical study of Pitinga cryolite mineralization through REE and Y analyses in disseminated and massive cryolite ore deposits, as well as in fluorite occurrences. REE signatures in fluorite and cryolite are similar to those in the Madeira albite granite. The highest ΣREE values are found in magmatic cryolite (677 to 1345 ppm); ΣREE is lower in massive cryolite. Average values for the different cryolite types are 10.3 ppm, 6.66 ppm and 8.38 ppm (for nucleated, caramel and white types, respectively). Disseminated fluorite displays higher ΣREE values (1708 and 1526ppm) than fluorite in late veins(34.81ppm). Yttrium concentration is higher in disseminated fluorite and in magmatic cryolite. The evolution of several parameters (REEtotal, LREE/HREE, Y) was followed throughout successive stages of evolution in albite granites and associated mineralization. At the end of the process, late cryolite was formed with low REEtotal content. REE data indicate that the MCD was formed by, and the disseminated ore enriched by (additional formation of hydrothermal disseminated cryolite), hydrothermal fluids, residual from albite granite. The presence of tetrads is poorly defined, although nucleated, caramel and white cryolite types show evidence for tetrad effect.

Determinação de minoxidil em formulações farmacêuticas usando permanganometria

Um método clássico para a determinação de minoxidil em formulações farmacêuticas é proposto baseado na reação redox entre KMnO4 e o minoxidil. Os melhores resultados na permanganometria foram obtidos usando concentrações de 1,00 x 10-2 mol L-1 para o permanganato. O minoxidil foi usado como titulante na concentração de 2,00 x 10-2 mol L-1 diluído em solução de H2SO4 2,00 mol L-1. As recuperações para método proposto foram da ordem de 94,5 a 95,2 % dependendo da amostra comercial. O método proposto foi aplicado à amostras comerciais contendo minoxidil e comparado com resultados obtidos a partir de procedimentos cromatográficos com erros relativos da ordem de -1 a -5,26%. O procedimento se mostrou simples, rápido e pode ser uma alternativa para a determinação de minoxidil em amostras farmacêuticas, nas quais a concentração do fármaco é relativamente elevada.

Contribution margin model applied to the marketing planning of a container liner carrier

The implementation of confidential contracts between a container liner carrier and its customers, because of the Ocean Shipping Reform Act (OSRA) 1998, demands a revision in the methodology applied in the carrier's planning of marketing and sales. The marketing and sales planning process should be more scientific and with a better use of operational research tools considering the selection of the customers under contracts, the duration of the contracts, the freight, and the container imbalances of these contracts are basic factors for the carrier's yield. This work aims to develop a decision support system based on a linear programming model to generate the business plan for a container liner carrier, maximizing the contribution margin of its freight.