Evaluation of the Efficiency of Line-Start Permanent-Magnet Machines as a Function of the Operating Temperature

The standard squirrel-cage induction machine has nearly reached its maximum efficiency. In order to further increase the energy efficiency of electrical machines, the use of permanent magnets in combination with the robust design and the line start capability of the induction machine is extensively investigated. Many experimental designs have been suggested in literature, but recently, these line-start permanent-magnet machines (LSPMMs) have become off-the-shelf products available in a power range up to 7.5 kW. The permanent magnet flux density is a function of the operating temperature. Consequently, the temperature will affect almost every electrical quantity of the machine, including current, torque, and efficiency. In this paper, the efficiency of an off-the-shelf 4-kW three-phase LSPMM is evaluated as a function of the temperature by both finite-element modeling and by practical measurements. In order to obtain stator, rotor, and permanent magnet temperatures, lumped thermal modeling is used.

Two-dimensional drift-diffusion simulation of organic solar cells

The aim of this master's thesis is to develop a two-dimensional drift-di usion model, which describes charge transport in organic solar cells. The main bene t of a two-dimensional model compared to a one-dimensional one is the inclusion of the nanoscale morphology of the active layer of a bulk heterojunction solar cell. The developed model was used to study recombination dynamics at the donor-acceptor interface. In some cases, it was possible to determine e ective parameters, which reproduce the results of the two-dimensional model in the one-dimensional case. A summary of the theory of charge transport in semiconductors was presented and discussed in the context of organic materials. Additionally, the normalization and discretization procedures required to nd a numerical solution to the charge transport problem were outlined. The charge transport problem was solved by implementing an iterative scheme called successive over-relaxation. The obtained solution is given as position-dependent electric potential, free charge carrier concentrations and current densities in the active layer. An interfacial layer, separating the pure phases, was introduced in order to describe charge dynamics occurring at the interface between the donor and acceptor. For simplicity, an e ective generation of free charge carriers in the interfacial layer was implemented. The pure phases simply act as transport layers for the photogenerated charges. Langevin recombination was assumed in the two-dimensional model and an analysis of the apparent recombination rate in the one-dimensional case is presented. The recombination rate in a two-dimensional model is seen to e ectively look like reduced Langevin recombination at open circuit. Replicating the J-U curves obtained in the two-dimensional model is, however, not possible by introducing a constant reduction factor in the Langevin recombination rate. The impact of an acceptor domain in the pure donor phase was investigated. Two cases were considered, one where the acceptor domain is isolated and another where it is connected to the bulk of the acceptor. A comparison to the case where no isolated domains exist was done in order to quantify the observed reduction in the photocurrent. The results show that all charges generated at the isolated domain are lost to recombination, but the domain does not have a major impact on charge transport. Trap-assisted recombination at interfacial trap states was investigated, as well as the surface dipole caused by the trapped charges. A theoretical expression for the ideality factor n_id as a function of generation was derived and shown to agree with simulation data. When the theoretical expression was fitted to simulation data, no interface dipole was observed.

Diffusion Monte Carlo study of electronic properties for H and Be atoms /

We examined three different algorithms used in diffusion Monte Carlo (DMC) to study their precisions and accuracies in predicting properties of isolated atoms, which are H atom ground state, Be atom ground state and H atom first excited state. All three algorithms — basic DMC, minimal stochastic reconfiguration DMC, and pure DMC, each with future-walking, are successfully impletmented in ground state energy and simple moments calculations with satisfactory results. Pure diffusion Monte Carlo with future-walking algorithm is proven to be the simplest approach with the least variance. Polarizabilities for Be atom ground state and H atom first excited state are not satisfactorily estimated in the infinitesimal differentiation approach. Likewise, an approach using the finite field approximation with an unperturbed wavefunction for the latter system also fails. However, accurate estimations for the a-polarizabilities are obtained by using wavefunctions that come from the time-independent perturbation theory. This suggests the flaw in our approach to polarizability estimation for these difficult cases rests with our having assumed the trial function is unaffected by infinitesimal perturbations in the Hamiltonian.

Exact property estimation from diffusion Monte Carlo with minimal stochastic reconfiguration /

Our objective is to develop a diffusion Monte Carlo (DMC) algorithm to estimate the exact expectation values, ($o|^|^o), of multiplicative operators, such as polarizabilities and high-order hyperpolarizabilities, for isolated atoms and molecules. The existing forward-walking pure diffusion Monte Carlo (FW-PDMC) algorithm which attempts this has a serious bias. On the other hand, the DMC algorithm with minimal stochastic reconfiguration provides unbiased estimates of the energies, but the expectation values ($o|^|^) are contaminated by ^, an user specified, approximate wave function, when A does not commute with the Hamiltonian. We modified the latter algorithm to obtain the exact expectation values for these operators, while at the same time eliminating the bias. To compare the efficiency of FW-PDMC and the modified DMC algorithms we calculated simple properties of the H atom, such as various functions of coordinates and polarizabilities. Using three non-exact wave functions, one of moderate quality and the others very crude, in each case the results are within statistical error of the exact values.

A comparison of functional behaviour assessment rating scales in a sample of children and youth with autism spectrum disorders

This study sought to compare the results of the Motivation Assessment Scale (MAS; Durand & Crimmins, 1988), Questions About Behavior Function Scale (QABF; Matson & Vollmer, 1996) and Functional Analysis Screening Tool (FAST; Iwata & Deleon, 1996), when completed by parent informants in a sample of children and youth with autism spectrum disorders (ASD) who display challenging behaviour. Results indicated that there was low agreement between the functional hypotheses derived from each of three measures. In addition, correlations between functionally analogous scales were substantially lower than expected, while correlations between non-analogous subscales were stronger than anticipated. As indicated by this study, clinicians choosing to use FBA questionnaires to assess behavioural function, may not obtain accurate functional hypotheses, potentially resulting in ineffective intervention plans. The current study underscores the caution that must be taken when asking parents to complete these questionnaires to determine the function(s) of challenging behaviour for children/youth with ASD.

Functional analysis and treatment of OCD-related behaviour in a child with Autism Spectrum Disorder

Research indicates that Obsessive-Compulsive Disorder (OCD; DSM-IV-TR, American Psychiatric Association, 2000) is the second most frequent disorder to coincide with Autism Spectrum Disorder (ASD; Leyfer et aI., 2006). Excessive collecting and hoarding are also frequently reported in children with ASD (Berjerot, 2007). Although functional analysis (Iwata, Dorsey, Slifer, Bauman, & Richman, 1982/1994) has successfully identified maintaining variables for repetitive behaviours such as of bizarre vocalizations (e.g., Wilder, Masuda, O'Connor, & Baham, 2001), tics (e.g., Scotti, Schulman, & Hojnacki, 1994), and habit disorders (e.g., Woods & Miltenberger, 1996), extant literature ofOCD and functional analysis methodology is scarce (May et aI., 2008). The current studies utilized functional analysis methodology to identify the types of operant functions associated with the OCD-related hoarding behaviour of a child with ASD and examined the efficacy of function-based intervention. Results supported hypotheses of automatic and socially mediated positive reinforcement. A corresponding function-based treatment plan incorporated antecedent strategies and differential reinforcement (Deitz, 1977; Lindberg, Iwata, Kahng, and DeLeon, 1999; Reynolds, 1961). Reductions in problem behaviour were evidenced through use of a multiple baseline across behaviours design and maintained during two-month follow-up. Decreases in symptom severity were also discerned through subjective measures of treatment effectiveness.

I Believe in me, not OCB: Evaluation of Group Function-Based CBT as a Treatment for Obsessive Compulsive Behaviour in Four Children with HFA

Researchers have conceptualized repetitive behaviours in individuals with Autism Spectrum Disorder (ASD) on a continuum oflower-Ievel, motoric, repetitive behaviours and higher-order, repetitive behaviours that include symptoms ofOCD (Hollander, Wang, Braun, & Marsh, 2009). Although obsessional, ritualistic, and stereotyped behaviours are a core feature of ASD, individuals with ASD frequently experience obsessions and compulsions that meet DSM-IV-TR (American Psychiatric Association, 2000) criteria for Obsessive-Compulsive Disorder (OCD). Given the acknowledged difficulty in differentiating between OCD and Autism-related obsessive-compulsive phenomena, the present study uses the term Obsessive Compulsive Behaviour (OCB) to represent both phenomena. This study used a multiple baseline design across behaviours and ABC designs (Cooper, Heron, & Heward, 2007) to investigate if a 9-week Group Function-Based Cognitive Behavioural Therapy (CBT) decreased OCB in four children (ages 7 - 11 years) with High Functioning Autism (HFA). Key treatment components included traditional CBT components (awareness training, cognitive-behavioural skills training, exposure and response prevention) as well as function-based assessment and intervention. Time series data indicated significant decreases in OCBs. Standardized assessments showed decreases in symptom severity, and increases in quality of life for the participants and their families. Issues regarding symptom presentation, assessment, and treatment of a dually diagnosed child are discussed.

Efficient estimation using the characteristic function : theory and applications with high frequency data

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Quantifying diffusion in biofilms : from model hydrogels to living biofilms

Les biofilms sont des communautés de microorganismes incorporés dans une matrice exo-polymérique complexe. Ils sont reconnus pour jouer un rôle important comme barrière de diffusion dans les systèmes environnementaux et la santé humaine, donnant lieu à une résistance accrue aux antibiotiques et aux désinfectants. Comme le transfert de masse dans un biofilm est principalement dû à la diffusion moléculaire, il est primordial de comprendre les principaux paramètres influençant les flux de diffusion. Dans ce travail, nous avons étudié un biofilm de Pseudomonas fluorescens et deux hydrogels modèles (agarose et alginate) pour lesquels l’autodiffusion (mouvement Brownien) et les coefficients de diffusion mutuels ont été quantifiés. La spectroscopie par corrélation de fluorescence a été utilisée pour mesurer les coefficients d'autodiffusion dans une volume confocal de ca. 1 m3 dans les gels ou les biofilms, tandis que les mesures de diffusion mutuelle ont été faites par cellule de diffusion. En outre, la voltamétrie sur microélectrode a été utilisée pour évaluer le potentiel de Donnan des gels afin de déterminer son impact sur la diffusion. Pour l'hydrogel d'agarose, les observations combinées d'une diminution du coefficient d’autodiffusion et de l’augmentation de la diffusion mutuelle pour une force ionique décroissante ont été attribuées au potentiel de Donnan du gel. Des mesures de l'effet Donnan (différence de -30 mV entre des forces ioniques de 10-4 et 10-1 M) et l'accumulation correspondante d’ions dans l'hydrogel (augmentation d’un facteur de 13 par rapport à la solution) ont indiqué que les interactions électrostatiques peuvent fortement influencer le flux de diffusion de cations, même dans un hydrogel faiblement chargé tel que l'agarose. Curieusement, pour un gel plus chargé comme l'alginate de calcium, la variation de la force ionique et du pH n'a donné lieu qu'à de légères variations de la diffusion de sondes chargées dans l'hydrogel. Ces résultats suggèrent qu’en influençant la diffusion du soluté, l'effet direct des cations sur la structure du gel (compression et/ou gonflement induits) était beaucoup plus efficace que l'effet Donnan. De même, pour un biofilm bactérien, les coefficients d'autodiffusion étaient pratiquement constants sur toute une gamme de force ionique (10-4-10-1 M), aussi bien pour des petits solutés chargés négativement ou positivement (le rapport du coefficient d’autodiffusion dans biofilm sur celui dans la solution, Db/Dw ≈ 85 %) que pour des nanoparticules (Db/Dw≈ 50 %), suggérant que l'effet d'obstruction des biofilms l’emporte sur l'effet de charge. Les résultats de cette étude ont montré que parmi les divers facteurs majeurs qui affectent la diffusion dans un biofilm environnemental oligotrophe (exclusion stérique, interactions électrostatiques et hydrophobes), les effets d'obstruction semblent être les plus importants lorsque l'on tente de comprendre la diffusion du soluté. Alors que les effets de charge ne semblaient pas être importants pour l'autodiffusion de substrats chargés dans l'hydrogel d'alginate ou dans le biofilm bactérien, ils ont joué un rôle clé dans la compréhension de la diffusion à travers l’agarose. L’ensemble de ces résultats devraient être très utiles pour l'évaluation de la biodisponibilité des contaminants traces et des nanoparticules dans l'environnement.

Étude du champ magnétique interne de deux matériaux magnétiques et d'un supraconducteur sans symétrie d'inversion.

Cette thèse est divisée en trois parties. Une première section présente les résultats de l'étude de la formation de polarons magnétiques liés (BMP) dans le ferroaimant EuB6 par diffusion de neutrons à petits angles (SANS). La nature magnétique du système ferromagnétique est observée sous une température critique de 15K. La signature des BMP n'apparaît pas dans la diffusion de neutrons, mais ces mesures permettent de confirmer une limite inférieure de 100\AA à la longueur de cohérence des BMP (xi_{Lower}). Dans un second temps, l'étude du LaRhSi3, un supraconducteur sans symétrie d'inversion, par muSR et ZF-muSR nous permet de sonder le comportement magnétique du système dans la phase supraconductrice. Aucun champ magnétique interne n'a été détecté en ZF-muSR sous la température critique (T_c = 2.2K). Cela indique que la phase supraconductrice ne porte pas de moment cinétique intrinsèque. L'analyse du spectre d'asymétrie sous l'application d'un champ magnétique externe nous apprend que le système est faiblement type II par l'apparition de la signature de domaines magnétiques typique d'un réseau de vortex entre H_{c1}(0) et H_{c2}(0), respectivement de 80+/- 5 et 169.0 +/- 0.5 G. Finalement, la troisième section porte sur l'étude du champ magnétique interne dans l'antiferroaimant organique NIT-2Py. L'observation d'une dépendance en température des champs magnétiques internes aux sites d'implantation muonique par ZF-muSR confirme la présence d'une interaction à longue portée entre les moments cinétiques moléculaires. Ces valeurs de champs internes, comparées aux calculs basés sur la densité de spins obtenue par calculs de la théorie de la fonctionnelle de la densité, indiquent que la moitié des molécules se dimérisent et ne contribuent pas à l'ordre antiferromagnétique. La fraction des molécules contribuant à l'ordre antiferromagnétique sous la température critique (T_c = 1.33 +/- 0.01K) forme des chaines uniformément polarisées selon l'axe (1 0 -2). Ces chaines interagissent antiferromagnétiquement entre elles le long de l'axe (0 1 0) et ferromagnétiquement entre les plan [-1 0 2].

Development of a Phase Separation Strategy in Macrocyclization Reactions

La réaction de macrocyclisation est une transformation fondamentale en chimie organique de synthèse. Le principal défi associcé à la formation de macrocycles est la compétition inhérente avec la réaction d’oligomérisation qui mène à la formation de sousproduits indésirables. De plus, l’utilisation de conditions de dilutions élevées qui sont nécessaires afin d’obtenir une cyclisation “sélective”, sont souvent décourageantes pour les applications à l’échelle industrielle. Malgré cet intérêt pour les macrocycles, la recherche visant à développer des stratégies environnementalement bénignes, qui permettent d’utiliser des concentrations normales pour leur synthèse, sont encore rares. Cette thèse décrit le développement d’une nouvelle approche générale visant à améliorer l’efficacité des réactions de macrocyclisation en utilisant le contrôle des effets de dilution. Une stratégie de “séparation de phase” qui permet de réaliser des réactions à des concentrations plus élevées a été developpée. Elle se base sur un mélange de solvant aggrégé contrôlé par les propriétés du poly(éthylène glycol) (PEG). Des études de tension de surface, spectroscopie UV et tagging chimique ont été réalisées afin d’élucider le mécanisme de “séparation de phase”. Il est proposé que celui-ci fonctionne par diffusion lente du substrat organique vers la phase ou le catalyseur est actif. La nature du polymère co-solvant joue donc un rôle crutial dans le contrôle de l’aggrégation et de la catalyse La stratégie de “séparation de phase” a initiallement été étudiée en utilisant le couplage oxidatif d’alcynes de type Glaser-Hay co-catalysé par un complexe de cuivre et de nickel puis a été transposée à la chimie en flux continu. Elle fut ensuite appliquée à la cycloaddition d’alcynes et d’azotures catalysée par un complexe de cuivre en “batch” ainsi qu’en flux continu.

Spectrum simulation of rough and nanostructured targets from their 2D and 3D image by Monte Carlo methods

Corteo is a program that implements Monte Carlo (MC) method to simulate ion beam analysis (IBA) spectra of several techniques by following the ions trajectory until a sufficiently large fraction of them reach the detector to generate a spectrum. Hence, it fully accounts for effects such as multiple scattering (MS). Here, a version of Corteo is presented where the target can be a 2D or 3D image. This image can be derived from micrographs where the different compounds are identified, therefore bringing extra information into the solution of an IBA spectrum, and potentially significantly constraining the solution. The image intrinsically includes many details such as the actual surface or interfacial roughness, or actual nanostructures shape and distribution. This can for example lead to the unambiguous identification of structures stoichiometry in a layer, or at least to better constraints on their composition. Because MC computes in details the trajectory of the ions, it simulates accurately many of its aspects such as ions coming back into the target after leaving it (re-entry), as well as going through a variety of nanostructures shapes and orientations. We show how, for example, as the ions angle of incidence becomes shallower than the inclination distribution of a rough surface, this process tends to make the effective roughness smaller in a comparable 1D simulation (i.e. narrower thickness distribution in a comparable slab simulation). Also, in ordered nanostructures, target re-entry can lead to replications of a peak in a spectrum. In addition, bitmap description of the target can be used to simulate depth profiles such as those resulting from ion implantation, diffusion, and intermixing. Other improvements to Corteo include the possibility to interpolate the cross-section in angle-energy tables, and the generation of energy-depth maps.

The Role of Diffusion in ISOL Targets for the Production of Radioactive Ion Beams

On line isotope separation techniques (ISOL) for production of ion beams of short-lived radionuclides require fast separation of nuclear reaction products from irradiated target materials followed by a transfer into an ion source. As a first step in this transport chain the release of nuclear reaction products from refractory metals has been studied systematically and will be reviewed. High-energy protons (500 - 1000 MeV) produce a large number of radionuclides in irradiated materials via the nuclear reactions spallation, fission and fragmentation. Foils and powders of Re, W, Ta, Hf, Mo, Nb, Zr, Y, Ti and C were irradiated with protons (600 - 1000 MeV) at the Dubna synchrocyclotron, the CERN synchrocyclotron and at the CERN PS-booster to produce different nuclear reaction products. The main topic of the paper is the determination of diffusion coefficients of the nuclear reaction products in the target matrix, data evaluation and a systematic interpretation of the data. The influence of the ionic radius of the diffusing species and the lattice type of the host material used as matrix or target on the diffusion will be evaluated from these systematics. Special attention was directed to the release of group I, II and III-elements. Arrhenius plots lead to activation energies of the diffusion process.

Studies on Heat Diffusion in Selected Conducting Polymers using Probe Beam Deflection and Photoacoustic Techniques

In the present study, radio frequency plasma polymerization technique is used to prepare thin films of polyaniline, polypyrrole, poly N-methyl pyrrole and polythiophene. The thermal characterization of these films is carried out using transverse probe beam deflection method. Electrical conductivity and band gaps are also determined. The effect of iodine doping on electrical conductivity and the rate of heat diffusion is explored.Bulk samples of poyaniline and polypyrrole in powder form are synthesized by chemical route. Open photoacoustic cell configuration is employed for the thermal characterization of these samples. The effect of acid doping on heat diffusion in these bulk samples of polyaniline is also investigated. The variation of electrical conductivity of doped polyaniline and polypyrrole with temperature is also studied for drawing conclusion on the nature of conduction in these samples. In order to improve the processability of polyaniline and polypyrrole, these polymers are incorporated into a host matrix of poly vinyl chloride. Measurements of thermal diffusivity and electrical conductivity of these samples are carried out to investigate the variation of these quantities as a function of the content of polyvinyl chloride.

Modeling and Analysis of Some Heavy Tailed Time Series

The thesis has covered various aspects of modeling and analysis of finite mean time series with symmetric stable distributed innovations. Time series analysis based on Box and Jenkins methods are the most popular approaches where the models are linear and errors are Gaussian. We highlighted the limitations of classical time series analysis tools and explored some generalized tools and organized the approach parallel to the classical set up. In the present thesis we mainly studied the estimation and prediction of signal plus noise model. Here we assumed the signal and noise follow some models with symmetric stable innovations.We start the thesis with some motivating examples and application areas of alpha stable time series models. Classical time series analysis and corresponding theories based on finite variance models are extensively discussed in second chapter. We also surveyed the existing theories and methods correspond to infinite variance models in the same chapter. We present a linear filtering method for computing the filter weights assigned to the observation for estimating unobserved signal under general noisy environment in third chapter. Here we consider both the signal and the noise as stationary processes with infinite variance innovations. We derived semi infinite, double infinite and asymmetric signal extraction filters based on minimum dispersion criteria. Finite length filters based on Kalman-Levy filters are developed and identified the pattern of the filter weights. Simulation studies show that the proposed methods are competent enough in signal extraction for processes with infinite variance.Parameter estimation of autoregressive signals observed in a symmetric stable noise environment is discussed in fourth chapter. Here we used higher order Yule-Walker type estimation using auto-covariation function and exemplify the methods by simulation and application to Sea surface temperature data. We increased the number of Yule-Walker equations and proposed a ordinary least square estimate to the autoregressive parameters. Singularity problem of the auto-covariation matrix is addressed and derived a modified version of the Generalized Yule-Walker method using singular value decomposition.In fifth chapter of the thesis we introduced partial covariation function as a tool for stable time series analysis where covariance or partial covariance is ill defined. Asymptotic results of the partial auto-covariation is studied and its application in model identification of stable auto-regressive models are discussed. We generalize the Durbin-Levinson algorithm to include infinite variance models in terms of partial auto-covariation function and introduce a new information criteria for consistent order estimation of stable autoregressive model.In chapter six we explore the application of the techniques discussed in the previous chapter in signal processing. Frequency estimation of sinusoidal signal observed in symmetric stable noisy environment is discussed in this context. Here we introduced a parametric spectrum analysis and frequency estimate using power transfer function. Estimate of the power transfer function is obtained using the modified generalized Yule-Walker approach. Another important problem in statistical signal processing is to identify the number of sinusoidal components in an observed signal. We used a modified version of the proposed information criteria for this purpose.