Denoising Your Monte Carlo Renders: Recent Advances in Image Space-Adaptive Sampling and Reconstruction

With the ongoing shift in the computer graphics industry toward Monte Carlo rendering, there is a need for effective, practical noise-reduction techniques that are applicable to a wide range of rendering effects and easily integrated into existing production pipelines. This course surveys recent advances in image-space adaptive sampling and reconstruction algorithms for noise reduction, which have proven very effective at reducing the computational cost of Monte Carlo techniques in practice. These approaches leverage advanced image-filtering techniques with statistical methods for error estimation. They are attractive because they can be integrated easily into conventional Monte Carlo rendering frameworks, they are applicable to most rendering effects, and their computational overhead is modest.

Healthy relationships: An HIV intervention for positives

The present study assessed Community Prevention Intervention Unit clients participating in Healthy Relationships in December of 2005 to December of 2006. Healthy Relationships was formulated from Social Cognitive Theory-based HIV prevention. This 5-week intervention integrates skills building, self-efficacy, and positive expectations about new behaviors in addition to stress reduction and sexual risk reduction techniques to elicit a behavior change. The study was undertaken to evaluate differences in attitudes, beliefs and behaviors regarding one's HIV status and participation in Healthy Relationships. Gender differences among participants in Healthy Relationships were also measured. Subjects were evaluated utilizing pre- and post-questionnaires. Analyses revealed that there were significant differences in some risk behaviors, beliefs and attitudes. However, men and women did differ with regard to significant differences among disclosure. ^

Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

HEALTH MAINTENANCE ORGANIZATION ENVIRONMENT: AN EMPIRICAL STUDY OF THE RELATIONSHIP OF EXTERNAL CONTEXT AND PERFORMANCE

The research project is an extension of a series of administrative science and health care research projects evaluating the influence of external context, organizational strategy, and organizational structure upon organizational success or performance. The research will rely on the assumption that there is not one single best approach to the management of organizations (the contingency theory). As organizational effectiveness is dependent on an appropriate mix of factors, organizations may be equally effective based on differing combinations of factors. The external context of the organization is expected to influence internal organizational strategy and structure and in turn the internal measures affect performance (discriminant theory). The research considers the relationship of external context and organization performance.^ The unit of study for the research will be the health maintenance organization (HMO); an organization the accepts in exchange for a fixed, advance capitation payment, contractual responsibility to assure the delivery of a stated range of health sevices to a voluntary enrolled population. With the current Federal resurgence of interest in the Health Maintenance Organization (HMO) as a major component in the health care system, attention must be directed at maximizing development of HMOs from the limited resources available. Increased skills are needed in both Federal and private evaluation of HMO feasibility in order to prevent resource investment and in projects that will fail while concurrently identifying potentially successful projects that will not be considered using current standards.^ The research considers 192 factors measuring contextual milieu (social, educational, economic, legal, demographic, health and technological factors). Through intercorrelation and principle components data reduction techniques this was reduced to 12 variables. Two measures of HMO performance were identified, they are (1) HMO status (operational or defunct), and (2) a principle components factor score considering eight measures of performance. The relationship between HMO context and performance was analysed using correlation and stepwise multiple regression methods. In each case it has been concluded that the external contextual variables are not predictive of success or failure of study Health Maintenance Organizations. This suggests that performance of an HMO may rely on internal organizational factors. These findings have policy implications as contextual measures are used as a major determinant in HMO feasibility analysis, and as a factor in the allocation of limited Federal funds. ^

Ordenaciones de material genético a partir de información multidimensional

Nuevas biotecnologías permiten obtener información para caracterizar materiales genéticos a partir de múltiples marcadores, ya sean éstos moleculares y/o morfológicos. La ordenación del material genético a través de la exploración de patrones de variabilidad multidimensionales se aborda mediante diversas técnicas de análisis multivariado. Las técnicas multivariadas de reducción de dimensión (TRD) y la representación gráfica de las mismas cobran sustancial importancia en la visualización de datos multivariados en espacios de baja dimensión ya que facilitan la interpretación de interrelaciones entre las variables (marcadores) y entre los casos u observaciones bajo análisis. Tanto el Análisis de Componentes Principales, como el Análisis de Coordenadas Principales y el Análisis de Procrustes Generalizado son TRD aplicables a datos provenientes de marcadores moleculares y/o morfológicos. Los Árboles de Mínimo Recorrido y los biplots constituyen técnicas para lograr representaciones geométricas de resultados provenientes de TRD. En este trabajo se describen estas técnicas multivariadas y se ilustran sus aplicaciones sobre dos conjuntos de datos, moleculares y morfológicos, usados para caracterizar material genético fúngico.

A scalable approach for content based image retrieval in cloud datacenter

The emergence of cloud datacenters enhances the capability of online data storage. Since massive data is stored in datacenters, it is necessary to effectively locate and access interest data in such a distributed system. However, traditional search techniques only allow users to search images over exact-match keywords through a centralized index. These techniques cannot satisfy the requirements of content based image retrieval (CBIR). In this paper, we propose a scalable image retrieval framework which can efficiently support content similarity search and semantic search in the distributed environment. Its key idea is to integrate image feature vectors into distributed hash tables (DHTs) by exploiting the property of locality sensitive hashing (LSH). Thus, images with similar content are most likely gathered into the same node without the knowledge of any global information. For searching semantically close images, the relevance feedback is adopted in our system to overcome the gap between low-level features and high-level features. We show that our approach yields high recall rate with good load balance and only requires a few number of hops.

Smart aeronautical structures: development and experimental validation of a structural health monitoring system for damage detection

En muchas áreas de la ingeniería, la integridad y confiabilidad de las estructuras son aspectos de extrema importancia. Estos son controlados mediante el adecuado conocimiento de danos existentes. Típicamente, alcanzar el nivel de conocimiento necesario que permita caracterizar la integridad estructural implica el uso de técnicas de ensayos no destructivos. Estas técnicas son a menudo costosas y consumen mucho tiempo. En la actualidad, muchas industrias buscan incrementar la confiabilidad de las estructuras que emplean. Mediante el uso de técnicas de última tecnología es posible monitorizar las estructuras y en algunos casos, es factible detectar daños incipientes que pueden desencadenar en fallos catastróficos. Desafortunadamente, a medida que la complejidad de las estructuras, los componentes y sistemas incrementa, el riesgo de la aparición de daños y fallas también incrementa. Al mismo tiempo, la detección de dichas fallas y defectos se torna más compleja. En años recientes, la industria aeroespacial ha realizado grandes esfuerzos para integrar los sensores dentro de las estructuras, además de desarrollar algoritmos que permitan determinar la integridad estructural en tiempo real. Esta filosofía ha sido llamada “Structural Health Monitoring” (o “Monitorización de Salud Estructural” en español) y este tipo de estructuras han recibido el nombre de “Smart Structures” (o “Estructuras Inteligentes” en español). Este nuevo tipo de estructuras integran materiales, sensores, actuadores y algoritmos para detectar, cuantificar y localizar daños dentro de ellas mismas. Una novedosa metodología para detección de daños en estructuras se propone en este trabajo. La metodología está basada en mediciones de deformación y consiste en desarrollar técnicas de reconocimiento de patrones en el campo de deformaciones. Estas últimas, basadas en PCA (Análisis de Componentes Principales) y otras técnicas de reducción dimensional. Se propone el uso de Redes de difracción de Bragg y medidas distribuidas como sensores de deformación. La metodología se validó mediante pruebas a escala de laboratorio y pruebas a escala real con estructuras complejas. Los efectos de las condiciones de carga variables fueron estudiados y diversos experimentos fueron realizados para condiciones de carga estáticas y dinámicas, demostrando que la metodología es robusta ante condiciones de carga desconocidas. ABSTRACT In many engineering fields, the integrity and reliability of the structures are extremely important aspects. They are controlled by the adequate knowledge of existing damages. Typically, achieving the level of knowledge necessary to characterize the structural integrity involves the usage of nondestructive testing techniques. These are often expensive and time consuming. Nowadays, many industries look to increase the reliability of the structures used. By using leading edge techniques it is possible to monitoring these structures and in some cases, detect incipient damage that could trigger catastrophic failures. Unfortunately, as the complexity of the structures, components and systems increases, the risk of damages and failures also increases. At the same time, the detection of such failures and defects becomes more difficult. In recent years, the aerospace industry has done great efforts to integrate the sensors within the structures and, to develop algorithms for determining the structural integrity in real time. The ‘philosophy’ has being called “Structural Health Monitoring” and these structures have been called “smart structures”. These new types of structures integrate materials, sensors, actuators and algorithms to detect, quantify and locate damage within itself. A novel methodology for damage detection in structures is proposed. The methodology is based on strain measurements and consists in the development of strain field pattern recognition techniques. The aforementioned are based on PCA (Principal Component Analysis) and other dimensional reduction techniques. The use of fiber Bragg gratings and distributed sensing as strain sensors is proposed. The methodology have been validated by using laboratory scale tests and real scale tests with complex structures. The effects of the variable load conditions were studied and several experiments were performed for static and dynamic load conditions, demonstrating that the methodology is robust under unknown load conditions.

Vibro-acoustic analysis of spacecraft structures with thin air layers

Esta Tesis presenta un estudio sobre el comportamiento vibroacústico de estructuras espaciales que incluyen capas de aire delgadas, así como sobre su modelización numérica. Las capas de aire pueden constituir un elemento fundamental en estos sistemas, como paneles solares plegados, que se consideran el caso de estudio en este trabajo. Para evaluar la influencia de las capas de aire en la respuesta dinámica del sistema se presenta el uso de modelos unidimensionales. La modelización de estos sistemas se estudia para los rangos de baja y alta frecuencia. En el rango de baja frecuencia se propone un conjunto de estrategias de simulación basadas en técnicas numéricas que se utilizan habitualmente en la industria aeroespacial para facilitar la aplicación de los resultados de la Tesis en los modelos numéricos actuales. Los resultados muestran el importante papel de las capas de aire en la respuesta del sistema. El uso de modelos basados en elementos finitos o de contorno para estos elementos proporciona resultados equivalentes aunque la aplicabilidad de estos últimos puede estar condicionada por la geometría del problema. Se estudia asimismo el uso del Análisis Estadístico de la Energía (SEA) para estos elementos. Una de las estrategias de simulación propuestas, que incluye una formulación energética para el aire que rodea a la estructura, se propone como estimador preliminar de la respuesta del sistema y sus frecuencias propias. Para el rango de alta frecuencia, se estudia la influencia de la definición del propio modelo SEA. Se presenta el uso de técnicas de reducción para determinar una matriz de pérdidas SEA reducida para definiciones incompletas del sistema (si algún elemento que interactúa con el resto no se incluye en el modelo). Esta nueva matriz tiene en cuenta la contribución de las subestructuras que no se consideran parte del modelo y que suelen ignorarse en el procedimiento habitual para reducir el tamaño del mismo. Esta matriz permite también analizar sistemas que incluyen algún componente con problemas de accesibilidad para medir su respuesta. Respecto a la determinación de los factores de pérdidas del sistema, se presenta una metodología que permite abordar casos en los que el método usual, el Método de Inyección de Potencia (PIM), no puede usarse. Se presenta un conjunto de métodos basados en la técnicas de optimización y de actualización de modelos para casos en los que no se puede medir la respuesta de todos los elementos del sistema y también para casos en los que no todos los elementos pueden ser excitados, abarcando un conjunto de casos más amplio que el abordable con el PIM. Para ambos rangos de frecuencia se presentan diferentes casos de análisis: modelos numéricos para validar los métodos propuestos y un panel solar plegado como caso experimental que pone de manifiesto la aplicación práctica de los métodos presentados en la Tesis. ABSTRACT This Thesis presents an study on the vibro-acoustic behaviour of spacecraft structures with thin air layers and their numerical modelling. The air layers can play a key role in these systems as solar wings in folded configuration that constitute the study case for this Thesis. A method based on one-dimensional models is presented to assess the influence of the air layers in the dynamic response of the system. The modelling of such systems is studied for low and high frequency ranges. In the low frequency range a set of modelling strategies are proposed based on numerical techniques used in the industry to facilitate the application of the results in the current numerical models. Results show the active role of the air layers in the system response and their great level of influence. The modelling of these elements by means of Finite Elements (FE) and Boundary Elements (BE) provide equivalent results although the applicability of BE models can be conditioned by the geometry of the problem. The use of Statistical Energy Analysis (SEA) for these systems is also presented. Good results on the system response are found for models involving SEA beyond the usual applicability limit. A simulation strategy, involving energetic formulation for the surrounding fluid is proposed as fast preliminary approach for the system response and the coupled eigenfrequencies. For the high frequency range, the influence of the definition of the SEA model is presented. Reduction techniques are used to determine a Reduced SEA Loss Matrix if the system definition is not complete and some elements, which interact with the rest, are not included. This new matrix takes into account the contribution of the subsystems not considered that are neglected in the usual approach for decreasing the size of the model. It also allows the analysis of systems with accessibility restrictions on some element in order to measure its response. Regarding the determination of the loss factors of a system, a methodology is presented for cases in which the usual Power Injection Method (PIM) can not be applied. A set of methods are presented for cases in which not all the subsystem responses can be measured or not all the subsystems can be excited, as solar wings in folded configuration. These methods, based on error minimising and model updating techniques can be used to calculate the system loss factors in a set of cases wider than the PIM’s. For both frequency ranges, different test problems are analysed: Numerical models are studied to validate the methods proposed; an experimental case consisting in an actual solar wing is studied on both frequency ranges to highlight the industrial application of the new methods presented in the Thesis.

Extended phone log-likelihood ratio features and acoustic-based I-vectors for language recognition

This paper presents new techniques with relevant improvements added to the primary system presented by our group to the Albayzin 2012 LRE competition, where the use of any additional corpora for training or optimizing the models was forbidden. In this work, we present the incorporation of an additional phonotactic subsystem based on the use of phone log-likelihood ratio features (PLLR) extracted from different phonotactic recognizers that contributes to improve the accuracy of the system in a 21.4% in terms of Cavg (we also present results for the official metric during the evaluation, Fact). We will present how using these features at the phone state level provides significant improvements, when used together with dimensionality reduction techniques, especially PCA. We have also experimented with applying alternative SDC-like configurations on these PLLR features with additional improvements. Also, we will describe some modifications to the MFCC-based acoustic i-vector system which have also contributed to additional improvements. The final fused system outperformed the baseline in 27.4% in Cavg.

Método computacional para la aceleración de análisis paramétricos de modificaciones locales en estructuras complejas sometidas a cargas dinámicas

Dentro del análisis y diseño estructural surgen frecuentemente problemas de ingeniería donde se requiere el análisis dinámico de grandes modelos de elementos finitos que llegan a millones de grados de libertad y emplean volúmenes de datos de gran tamaño. La complejidad y dimensión de los análisis se dispara cuando se requiere realizar análisis paramétricos. Este problema se ha abordado tradicionalmente desde diversas perspectivas: en primer lugar, aumentando la capacidad tanto de cálculo como de memoria de los sistemas informáticos empleados en los análisis. En segundo lugar, se pueden simplificar los análisis paramétricos reduciendo su número o detalle y por último se puede recurrir a métodos complementarios a los elementos .nitos para la reducción de sus variables y la simplificación de su ejecución manteniendo los resultados obtenidos próximos al comportamiento real de la estructura. Se propone el empleo de un método de reducción que encaja en la tercera de las opciones y consiste en un análisis simplificado que proporciona una solución para la respuesta dinámica de una estructura en el subespacio modal complejo empleando un volumen de datos muy reducido. De este modo se pueden realizar análisis paramétricos variando múltiples parámetros, para obtener una solución muy aproximada al objetivo buscado. Se propone no solo la variación de propiedades locales de masa, rigidez y amortiguamiento sino la adición de grados de libertad a la estructura original para el cálculo de la respuesta tanto permanente como transitoria. Adicionalmente, su facilidad de implementación permite un control exhaustivo sobre las variables del problema y la implementación de mejoras como diferentes formas de obtención de los autovalores o la eliminación de las limitaciones de amortiguamiento en la estructura original. El objetivo del método se puede considerar similar a los que se obtienen al aplicar el método de Guyan u otras técnicas de reducción de modelos empleados en dinámica estructural. Sin embargo, aunque el método permite ser empleado en conjunción con otros para obtener las ventajas de ambos, el presente procedimiento no realiza la condensación del sistema de ecuaciones, sino que emplea la información del sistema de ecuaciones completa estudiando tan solo la respuesta en las variables apropiadas de los puntos de interés para el analista. Dicho interés puede surgir de la necesidad de obtener la respuesta de las grandes estructuras en unos puntos determinados o de la necesidad de modificar la estructura en zonas determinadas para cambiar su comportamiento (respuesta en aceleraciones, velocidades o desplazamientos) ante cargas dinámicas. Por lo tanto, el procedimiento está particularmente indicado para la selección del valor óptimo de varios parámetros en grandes estructuras (del orden de cientos de miles de modos) como pueden ser la localización de elementos introducidos, rigideces, masas o valores de amortiguamientos viscosos en estudios previos en los que diversas soluciones son planteadas y optimizadas, y que en el caso de grandes estructuras, pueden conllevar un número de simulaciones extremadamente elevado para alcanzar la solución óptima. Tras plantear las herramientas necesarias y desarrollar el procedimiento, se propone un caso de estudio para su aplicación al modelo de elementos .nitos del UAV MILANO desarrollado por el Instituto Nacional de Técnica Aeroespacial. A dicha estructura se le imponen ciertos requisitos al incorporar un equipo en aceleraciones en punta de ala izquierda y desplazamientos en punta de ala derecha en presencia de la sustentación producida por una ráfaga continua de viento de forma sinusoidal. La modificación propuesta consiste en la adición de un equipo en la punta de ala izquierda, bien mediante un anclaje rígido, bien unido mediante un sistema de reducción de la respuesta dinámica con propiedades de masa, rigidez y amortiguamiento variables. El estudio de los resultados obtenidos permite determinar la optimización de los parámetros del sistema de atenuación por medio de múltiples análisis dinámicos de forma que se cumplan de la mejor forma posible los requisitos impuestos con la modificación. Se comparan los resultados con los obtenidos mediante el uso de un programa comercial de análisis por el método de los elementos .nitos lográndose soluciones muy aproximadas entre el modelo completo y el reducido. La influencia de diversos factores como son el amortiguamiento modal de la estructura original, el número de modos retenidos en la truncatura o la precisión proporcionada por el barrido en frecuencia se analiza en detalle para, por último, señalar la eficiencia en términos de tiempo y volumen de datos de computación que ofrece el método propuesto en comparación con otras aproximaciones. Por lo tanto, puede concluirse que el método propuesto se considera una opción útil y eficiente para el análisis paramétrico de modificaciones locales en grandes estructuras. ABSTRACT When developing structural design and analysis some projects require dynamic analysis of large finite element models with millions of degrees of freedom which use large size data .les. The analysis complexity and size grow if a parametric analysis is required. This problem has been approached traditionally in several ways: one way is increasing the power and the storage capacity of computer systems involved in the analysis. Other obvious way is reducing the total amount of analyses and their details. Finally, complementary methods to finite element analysis can also be employed in order to limit the number of variables and to reduce the execution time keeping the results as close as possible to the actual behaviour of the structure. Following this third option, we propose a model reduction method that is based in a simplified analysis that supplies a solution for the dynamic response of the structure in the complex modal space using few data. Thereby, parametric analysis can be done varying multiple parameters so as to obtain a solution which complies with the desired objetive. We propose not only mass, stiffness and damping variations, but also addition of degrees of freedom to the original structure in order to calculate the transient and steady-state response. Additionally, the simple implementation of the procedure allows an in-depth control of the problem variables. Furthermore, improvements such as different ways to obtain eigenvectors or to remove damping limitations of the original structure are also possible. The purpose of the procedure is similar to that of using the Guyan or similar model order reduction techniques. However, in our method we do not perform a true model order reduction in the traditional sense. Furthermore, additional gains, which we do not explore herein, can be obtained through the combination of this method with traditional model-order reduction procedures. In our procedure we use the information of the whole system of equations is used but only those nodes of interest to the analyst are processed. That interest comes from the need to obtain the response of the structure at specific locations or from the need to modify the structure at some suitable positions in order to change its behaviour (acceleration, velocity or displacement response) under dynamic loads. Therefore, the procedure is particularly suitable for parametric optimization in large structures with >100000 normal modes such as position of new elements, stiffness, mass and viscous dampings in previous studies where different solutions are devised and optimized, and in the case of large structures, can carry an extremely high number of simulations to get the optimum solution. After the introduction of the required tools and the development of the procedure, a study case is proposed with use the finite element model (FEM) of the MILANO UAV developed by Instituto Nacional de Técnica Aeroespacial. Due to an equipment addition, certain acceleration and displacement requirements on left wing tip and right wing tip, respectively, are imposed. The structure is under a continuous sinusoidal wind gust which produces lift. The proposed modification consists of the addition of an equipment in left wing tip clamped through a rigid attachment or through a dynamic response reduction system with variable properties of mass, stiffness and damping. The analysis of the obtained results allows us to determine the optimized parametric by means of multiple dynamic analyses in a way such that the imposed requirements have been accomplished in the best possible way. The results achieved are compared with results from a commercial finite element analysis software, showing a good correlation. Influence of several factors such as the modal damping of the original structure, the number of modes kept in the modal truncation or the precission given by the frequency sweep is analyzed. Finally, the efficiency of the proposed method is addressed in tems of computational time and data size compared with other approaches. From the analyses performed, we can conclude that the proposed method is a useful and efficient option to perform parametric analysis of possible local modifications in large structures.

Estudo da intensificação da coalescência de emulsões de água em óleo com a aplicação de onda estacionária de ultrassom.

Considerando que o petróleo quando extraído dos poços em águas profundas chega a ter teor de água superior a 50% e que antes de ser enviado à refinaria deve ter uma quantidade de água inferior a 1%, torna-se necessário o uso de técnicas de redução da quantidade de água. Durante a extração do petróleo formam-se emulsões de água em óleo que são muito estáveis devido a um filme interfacial contendo asfaltenos e/ou resinas ao redor das gotas de água. Nesse trabalho é apresentada a utilização de ondas estacionárias de ultrassom para realizar a quebra dessas emulsões. Quando gotículas de água com dimensões da ordem de 10m, muito menores que o comprimento de onda, são submetidas a um campo acústico estacionário em óleo, a força de radiação acústica empurra as gotículas para os nós de pressão da onda. Uma célula de coalescência com frequência central ao redor de 1 MHz, constituída por quatro camadas sendo uma piezelétrica, uma de acoplamento sólido, uma com o líquido e outra refletora, foi modelada empregando o método da matriz de transferência, que permite calcular a impedância elétrica em função da frequência. Para minimizar o efeito do gradiente de temperatura entre a entrada e a saída da cavidade da célula, quando está em operação, foram utilizados dois transdutores piezelétricos posicionados transversalmente ao fluxo que são excitados e controlados independentemente. Foi implementado um controlador digital para ajustar a frequência e a potência de cada transdutor. O controlador tem como entrada o módulo e a fase da corrente elétrica no transdutor e como saída a amplitude da tensão elétrica e a frequência. Para as células desenvolvidas, o algoritmo de controle segue um determinado pico de ressonância no interior da cavidade da célula no intervalo de frequência de 1,09 a 1,15 MHz. A separação acústica de emulsões de água em óleo foi realizada em uma planta de laboratório de processamento de petróleo no CENPES/PETROBRAS. Foram testados a variação da quantidade de desemulsificante, o teor inicial de água na emulsão e a influência da vazão do sistema, com uma potência de 80 W. O teor final de água na emulsão mostrou que a aplicação de ultrassom aumentou a coalescência de água da emulsão, em todas as condições testadas, quando comparada a um teste sem aplicação de ultrassom. Identificou-se o tempo de residência no interior da célula de separação como um fator importante no processo de coalescência de emulsões de água e óleo. O uso de desemulsificante químico é necessário para realizar a separação, porém, em quantidades elevadas implicaria no uso de processos adicionais antes do repasse final do petróleo à refinaria. Os teores iniciais de água na emulsão de 30 e 50% indicam que o uso da onda estacionária na coalescência de emulsões não tem limitação quanto a esse parâmetro. De acordo com os resultados obtidos em laboratório, essa técnica seria indicada como uma alternativa para integrar um sistema de processamento primário em conjunto com um separador eletrostático.

A study on the flow characteristics of an industrial radiant tube burner

The thesis presents an experimentally validated modelling study of the flow of combustion air in an industrial radiant tube burner (RTB). The RTB is used typically in industrial heat treating furnaces. The work has been initiated because of the need for improvements in burner lifetime and performance which are related to the fluid mechanics of the com busting flow, and a fundamental understanding of this is therefore necessary. To achieve this, a detailed three-dimensional Computational Fluid Dynamics (CFD) model has been used, validated with experimental air flow, temperature and flue gas measurements. Initially, the work programme is presented and the theory behind RTB design and operation in addition to the theory behind swirling flows and methane combustion. NOx reduction techniques are discussed and numerical modelling of combusting flows is detailed in this section. The importance of turbulence, radiation and combustion modelling is highlighted, as well as the numerical schemes that incorporate discretization, finite volume theory and convergence. The study first focuses on the combustion air flow and its delivery to the combustion zone. An isothermal computational model was developed to allow the examination of the flow characteristics as it enters the burner and progresses through the various sections prior to the discharge face in the combustion area. Important features identified include the air recuperator swirler coil, the step ring, the primary/secondary air splitting flame tube and the fuel nozzle. It was revealed that the effectiveness of the air recuperator swirler is significantly compromised by the need for a generous assembly tolerance. Also, there is a substantial circumferential flow maldistribution introduced by the swirier, but that this is effectively removed by the positioning of a ring constriction in the downstream passage. Computations using the k-ε turbulence model show good agreement with experimentally measured velocity profiles in the combustion zone and proved the use of the modelling strategy prior to the combustion study. Reasonable mesh independence was obtained with 200,000 nodes. Agreement was poorer with the RNG  k-ε and Reynolds Stress models. The study continues to address the combustion process itself and the heat transfer process internal to the RTB. A series of combustion and radiation model configurations were developed and the optimum combination of the Eddy Dissipation (ED) combustion model and the Discrete Transfer (DT) radiation model was used successfully to validate a burner experimental test. The previously cold flow validated k-ε turbulence model was used and reasonable mesh independence was obtained with 300,000 nodes. The combination showed good agreement with temperature measurements in the inner and outer walls of the burner, as well as with flue gas composition measured at the exhaust. The inner tube wall temperature predictions validated the experimental measurements in the largest portion of the thermocouple locations, highlighting a small flame bias to one side, although the model slightly over predicts the temperatures towards the downstream end of the inner tube. NOx emissions were initially over predicted, however, the use of a combustion flame temperature limiting subroutine allowed convergence to the experimental value of 451 ppmv. With the validated model, the effectiveness of certain RTB features identified previously is analysed, and an analysis of the energy transfers throughout the burner is presented, to identify the dominant mechanisms in each region. The optimum turbulence-combustion-radiation model selection was then the baseline for further model development. One of these models, an eccentrically positioned flame tube model highlights the failure mode of the RTB during long term operation. Other models were developed to address NOx reduction and improvement of the flame profile in the burner combustion zone. These included a modified fuel nozzle design, with 12 circular section fuel ports, which demonstrates a longer and more symmetric flame, although with limited success in NOx reduction. In addition, a zero bypass swirler coil model was developed that highlights the effect of the stronger swirling combustion flow. A reduced diameter and a 20 mm forward displaced flame tube model shows limited success in NOx reduction; although the latter demonstrated improvements in the discharge face heat distribution and improvements in the flame symmetry. Finally, Flue Gas Recirculation (FGR) modelling attempts indicate the difficulty of the application of this NOx reduction technique in the Wellman RTB. Recommendations for further work are made that include design mitigations for the fuel nozzle and further burner modelling is suggested to improve computational validation. The introduction of fuel staging is proposed, as well as a modification in the inner tube to enhance the effect of FGR.

Studies on the generalisation of Gaussian processes and Bayesian neural networks

The assessment of the reliability of systems which learn from data is a key issue to investigate thoroughly before the actual application of information processing techniques to real-world problems. Over the recent years Gaussian processes and Bayesian neural networks have come to the fore and in this thesis their generalisation capabilities are analysed from theoretical and empirical perspectives. Upper and lower bounds on the learning curve of Gaussian processes are investigated in order to estimate the amount of data required to guarantee a certain level of generalisation performance. In this thesis we analyse the effects on the bounds and the learning curve induced by the smoothness of stochastic processes described by four different covariance functions. We also explain the early, linearly-decreasing behaviour of the curves and we investigate the asymptotic behaviour of the upper bounds. The effect of the noise and the characteristic lengthscale of the stochastic process on the tightness of the bounds are also discussed. The analysis is supported by several numerical simulations. The generalisation error of a Gaussian process is affected by the dimension of the input vector and may be decreased by input-variable reduction techniques. In conventional approaches to Gaussian process regression, the positive definite matrix estimating the distance between input points is often taken diagonal. In this thesis we show that a general distance matrix is able to estimate the effective dimensionality of the regression problem as well as to discover the linear transformation from the manifest variables to the hidden-feature space, with a significant reduction of the input dimension. Numerical simulations confirm the significant superiority of the general distance matrix with respect to the diagonal one.In the thesis we also present an empirical investigation of the generalisation errors of neural networks trained by two Bayesian algorithms, the Markov Chain Monte Carlo method and the evidence framework; the neural networks have been trained on the task of labelling segmented outdoor images.

Pyrolysis liquids and gases as alternative fuels in internal combustion engines:a review

Liquids and gases produced through biomass pyrolysis have potential as renewable fuels to replace fossil fuels in conventional internal combustion engines. This review compares the properties of pyrolysis fuels, produced from a variety of feedstocks and using different pyrolysis techniques, against those of fossil fuels. High acidity, the presence of solid particles, high water content, high viscosity, storage and thermal instability, and low energy content are typical characteristics of pyrolysis liquids. A survey of combustion, performance and exhaust emission results from the use of pyrolysis liquids (both crude and up-graded) in compression ignition engines is presented. With only a few exceptions, most authors have reported difficulties associated with the adverse properties of pyrolysis liquids, including: corrosion and clogging of the injectors, long ignition delay and short combustion duration, difficulty in engine start-up, unstable operation, coking of the piston and cylinders and subsequent engine seizure. Pyrolysis gas can be used more readily, either in spark ignition or compression ignition engines; however, NO reduction techniques are desirable. Various approaches to improve the properties of pyrolysis liquids are discussed and a comparison of the properties of up-graded vs. crude pyrolysis liquid is included. Further developments in up-gradation techniques, such as hydrocracking and bio-refinery approaches, could lead to the production of green diesel and green gasoline. Modifications required to engines for use with pyrolysis liquids, for example in the fuel supply and injection systems, are discussed. Storage stability and economic issues are also reviewed. Our study presents recent progress and important R&D areas for successful future use of pyrolysis fuels in internal combustion engines.

Highly photosensitive polymethyl methacrylate microstructured polymer optical fiber with doped core

In this Letter, we report the fabrication of a highly photosensitive, microstructured polymer optical fiber using benzyl dimethyl ketal as a dopant, as well as the inscription of a fiber Bragg grating in the fiber. A refractive index change in the core of at least 3.2 × 10 has been achieved, providing a grating with a strong transmission rejection of -23 dB with an inscription time of only 13 min. The fabrication method has a big advantage compared to doping step index fiber since it enables doping of the fiber without using extra dopants to compensate for the index reduction in the core introduced by the photosensitive agent. © 2013 Optical Society of America.