In the present thesis, we propose and investigate a new approach to diagnose the effects of the various degradation mechanisms, including thermal degradation at hot spots, winding deformations due to the mechanical forces from short circuit currents, partial discharges due to local electric field surges, and increased moisture levels in the cellulose insulation due to decomposition, that affect electric power transformers during their normal operation in an electric power grid. Although the proposed diagnostics method can in principle be used to detect various degradation mechanisms mentioned above, we focus in the present thesis on mechanical deformations of transformer winding structures. Such mechanical deformations are most often caused by mechanical forces from short circuit currents, but they may also be caused by initial manufacturing errors and inconsistencies not detected by the power transformers’ suppliers quality assurance processes. We model a transformer winding surrounded by the transformer-tank wall and the magnetic core as a two-dimensional parallel plate waveguide or as a three-dimensional coaxial waveguide, where one metallic boundary (plate or cylinder) represents the wall of the transformer tank and the other metallic boundary (plate or cylinder) represents the iron core that conducts the magnetic flux. In between there is a set of parallel or coaxial conductors representing the winding segments. The new principle proposed in the present thesis is to insert a number of antennas into a transformer tank to radiate and measure microwave fields interacting with metallic structures and insulation. The responses from the emitted microwave radiation are expected to be sensitive to material properties that reflect the changes caused by any harmful deterioration processes mentioned above. Specifically, we investigate the mechanical deformations of transformer winding structures by determining the locations of the individual winding segments or turns, using measurements of the scattered fields at both ends of the winding structure. We solve the propagation problem using conventional waveguide theory, including mode-matching and cascading techniques. The inverse problem is solved using modified steepest-descent optimization methods. The optimization model is tested by comparing our calculated scattering data with synthetic measurement data generated by the commercial program HFSS. A good agreement is obtained between the calculated and measured positions of winding segments for a number of studied cases, which indicates that the diagnostics method proposed in the present thesis couldbe potentially useful as a basis for the design of a future commercial on-line winding monitoring device. However, further development of the theoretical analysis of a number of typical winding deformations, improvements of the optimization algorithms and a practical study with measurements on an actual power transformer structure are all needed to make an attempt to design a commercial winding monitoring device feasible. / <p>QC 20131007</p>

Cell modulus and prestress are important determinants of cell behavior. This study creates new software tools to compute the modulus and prestress distribution within a living cell. As input, we have a sequence of images of a cell plated on a substrate with fluorescently labeled fibronectin dots. The cell generates focal adhesions with the dots and thus deforms the substrate. A sequence of images of the cell and the fibronectin dots shows their deformation. We tested three different ways to track the movement of the fluorescent fibronectin dots. We demonstrated the accuracy and the adaptability of each method on a sequence of test images with a rigid movement. We found the best method for dot tracking is a combination of successive dot identification and digital image correlation. The dot deformation provides a measure of traction forces acting on the cell. From traction forces thus inferred, we use FEM to compute the stress distribution within a cell. We consider two approaches. The first is based on the assumption that the cell has homogeneous elastic properties. This is straightforward and requires only the cell being meshed and the linear elasticity problem solved on that mesh. Second, we relaxed the homogeneity assumption. We used previously published correlations between prestress and modulus to iteratively update the modulus and prestress distributions within the cell. A novel feature of this work is the implicit reconstruction of the modulus distribution without a measured displacement field, and the reconstruction of the prestress distribution accounting for intracellular inhomogeneity.

The aim of this report is to study how machine learning can be used to reconstruct 2 dimensional computed tomography images from limited angle data. This could be used in a variety of applications where either the space or timeavailable for the CT scan limits the acquired data.In this study, three different types of models are considered. The first model uses filtered back projection (FBP) with a single learned filter, while the second uses a combination of multiple FBP:s with learned filters. The last model instead uses an FNO (Fourieer Neural Operator) layer to both inpaint and filter the limited angle data followed by a backprojection layer. The quality of the reconstructions are assessed both visually and statistically, using PSNR and SSIM measures.The results of this study show that while an FBP-based model using one or more trainable filter(s) can achieve better reconstructions than ones using an analytical Ram-Lak filter, their reconstructions still fail for small angle spans. Better results in the limited angle case can be achieved using the FNO-basedmodel.

In applied mechanics it is always necessary to understand the fundamental properties of a system in order to generate an accurate numerical model or to predict future operating conditions. These fundamental properties include, but are not limited to, the material parameters of a specimen, the boundary conditions inside of a system, or essential dimensional characteristics that define the system or body. However in certain instances there may be little to no knowledge about the systems conditions or properties; as a result the problem cannot be modeled accurately using standard numerical methods. Consequently, it is critical to define an approach that is capable of identifying such characteristics of the problem at hand. In this thesis, an inverse approach is formulated using proper orthogonal decomposition (POD) with an accompanying radial basis function (RBF) network to estimate the current material parameters of a specimen with little prior knowledge of the system. Specifically conductive heat transfer and linear elasticity problems are developed in this thesis and modeled with a corresponding finite element (FEM) or boundary element (BEM) method. In order to create the truncated POD-RBF network to be utilized in the inverse approach, a series of direct FEM or BEM solutions are used to generate a statistical data set of temperatures or deformations in the system or body, each having a set of various material parameters. The data set is then transformed via POD to generate an orthonormal basis to accurately solve for the desired material characteristics using the Levenberg-Marquardt (LM) algorithm. For now, the LM algorithm can be simply defined as a direct relation to the minimization of the Euclidean norm of the objective Least Squares function(s). The trained POD-RBF inverse technique outlined in this thesis provides a flexible by which this inverse approach can be implemented into various fields of engineering and mechanics. More importantly this approach is designed to offer an inexpensive way to accurately estimate material characteristics or properties using nondestructive techniques. While the POD-RBF inverse approach outlined in this thesis focuses primarily in application to conduction heat transfer, elasticity, and fracture mechanics, this technique is designed to be directly applicable to other realistic conditions and/or industries.

To accurately model or predict future operating conditions of a system in engineering or applied mechanics, it is necessary to understand its fundamental principles. These may be the material parameters, defining dimensional characteristics, or the boundary conditions. However, there are instances when there is little to no prior knowledge of the system properties or conditions, and consequently, the problem cannot be modeled accurately. It is therefore critical to define a method that can identify the desired characteristics of the current system without accumulating extensive computation time. This thesis formulates an inverse approach using proper orthogonal decomposition (POD) with an accompanying radial basis function (RBF) interpolation network. This method is capable of predicting the desired characteristics of a specimen even with little prior knowledge of the system. This thesis first develops a conductive heat transfer problem, and by using the truncated POD – RBF interpolation network, temperature values are predicted given a varying Biot number. Then, a simple bifurcation problem is modeled and solved for velocity profiles while changing the mass flow rate. This bifurcation problem provides the data and foundation for future research into the left ventricular assist device (LVAD) and implementation of POD – RBF. The trained POD – RBF inverse approach defined in this thesis can be implemented in several applications of engineering and mechanics. It provides model reduction, error filtration, regularization and an improvement over previous analysis utilizing computational fluid dynamics (CFD).

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This thesis develops an immersed finite element (IFE) space for numerical simulations arising from beam design with multiple materials. This IFE space is based upon meshes that can be independent of interface of the materials used to form a beam. Both the forward and inverse problems associated with the beam equation are considered. The order of accuracy of this IFE space is numerically investigated from the point of view of both the interpolation and finite element solution of the interface boundary value problems. Both single and multiple interfaces are considered in our numerical simulation. The results demonstrate that this IFE space has the optimal order of approximation capability. / Master of Science

[EN] The behavior of the heart is governed by electrical currents generated in the myocardium, and therefore, the study of the cardiac electrical activity is essential for the diagnosis of cardiac diseases. The forward problem of the electrocardiography (FP) entails the calculation of the torso potentials from the electrical activity of the heart and the 3D body model, while the inverse problem (IP) resolution allows the noninvasive reconstruction of the electrical activity of the heart from surface potentials. The IP is of great importance in clinical applications since it allows estimating the electrical activity of the myocardium with only noninvasive recordings. However, IP resolution is still a big challenge in electrocardiography since it is ill-posed, very unstable and has multiple solutions. In this thesis different algorithms and strategies based on the IP resolution were developed and applied in the noninvasive diagnosis of ventricular and atrial arrhythmias and evaluated with mathematical cellular models and clinical data bases. The thesis focuses on the IP resolution for the noninvasive reconstruction of the myocardial electrical activity for different diseases and propagation patterns, implementing a novel system for complex propagation patterns. The obtained results and propagation patterns were evaluated and classified with the corresponding optimal resolution strategy that minimizes the error and increases the stability of the system, proving its advantages and disadvantages depending on the different diseases and their activation pattern. A novel iterative method was implemented for the IP dipolar resolution optimized for representing simple propagation patterns, achieving a high stability and robustness against noise by constraining the solution to a limited number of dipoles. However, propagation patterns not representable by few dipoles need to be computed with the IP in terms of epicardial solutions which provide a more detailed estimation of the myocardial activity. IP resolution in the voltage and phase domains showed a good accuracy for simple and organized propagation patterns. This method allowed the noninvasive diagnosis of the Brugada syndrome or the location of ectopic focus in atrial arrhythmias by performing a parametric analysis of the electrograms morphology or the activation map reconstruction. However, mathematical and patient results presented in this thesis proved that, for complex propagation patterns like atrial fibrillation (AF), inverse solutions in the voltage and phase domains are over-smoothed and over-optimistic, simplifying the complex AF activity, leading to non-physiological results that do not match with the complex intracardiac electrograms recorded in AF patients. In this thesis, we proposed a novel technique for the noninvasive identification and location of high dominant frequency AF sources, based on the assumption that in many cases atrial drivers present the highest activation rate with an intermittent propagation to the rest of the tissue that activates at a slower rate. Although, voltage and phase inverse solutions for AF complex propagation patterns were over smoothed and inaccurate, the noninvasive estimation of frequency maps was significantly more accurate, allowing the identification of the AF frequency gradient and location of high frequency sources. This technique may help in planning ablation procedures, avoiding unnecessary interseptal punctures for right-to-left frequency gradients cases and facilitating the targeting of the AF drivers, reducing risk and time of the clinical procedure. / [ES] El comportamiento del corazón se rige por corrientes eléctricas generadas en el miocardio y, por lo tanto, el estudio de su actividad eléctrica es esencial para el diagnóstico de enfermedades cardíacas. El problema directo (PD) de la electrocardiografía implica el cálculo de los potenciales del torso a partir de la actividad eléctrica del corazón y el modelo 3D del cuerpo, mientras que la resolución del problema inverso (PI) permite la reconstrucción no invasiva de la actividad eléctrica del corazón a partir de los potenciales de superficie, cobrando una gran importancia en la práctica clínica. Sin embargo, sigue siendo un gran desafío para la electrocardiografía ya que está mal planteado, es muy inestable y tiene múltiples soluciones. A lo largo de esta tesis se han desarrollado diferentes estrategias para la resolución del PI, aplicándolas en el diagnóstico no invasivo de arritmias ventriculares y auriculares, verificándolas mediante modelos celulares matemáticos y bases de datos clínicas. La tesis se centra en la resolución del PI para la reconstrucción no invasiva de la actividad eléctrica del miocardio para diferentes enfermedades cardiacas con diferentes patrones de propagación, implementando un novedoso sistema para patrones de propagación complejos. Además, se han validado los resultados obtenidos y se han clasificado los diferentes patrones de propagación con la estrategia de resolución del PI óptima que minimice el error y aumente la estabilidad del sistema. Un nuevo método iterativo fue implementado para la resolución del PI para fuentes dipolares, siendo óptimo para representar patrones de propagación simples, logrando una alta estabilidad e inmunidad al ruido al restringir la solución a un número limitado de dipolos. Sin embargo, los patrones de propagación que no pueden ser representados por un número limitado de dipolos deben calcularse mediante la resolución del PI en términos de potenciales epicárdicos, proporcionando una estimación más detallada de la actividad del miocardio. La resolución del PI en el dominio de la tensión y fase mostró ser muy preciso para patrones de propagación simples y organizados. Este método permite el diagnóstico no invasivo del síndrome de Brugada o la ubicación de focos ectópicos en arritmias auriculares mediante un análisis paramétrico de la morfología de los electrogramas o la reconstrucción de los mapas de activación. Sin embargo, los resultados matemáticos y clínicos presentados en esta tesis demostraron que, para patrones de propagación complejos como la fibrilación auricular (FA), los resultados obtenidos mediante la resolución del PI en el dominio de la tensión y fase son demasiado suaves y optimistas, simplificando enormemente la complejidad de la FA, llevando a resultados no fisiológicos que no coinciden con la actividad compleja de los electrogramas intracardiacos registrados en pacientes con FA. En esta tesis, se ha propuesto una novedosa técnica para la identificación y localización no invasiva de fuentes con una frecuencia dominante alta, basado en la suposición de que en muchos casos las fuentes eléctricas que generan y mantienen la FA presentan una tasa de activación más alta, con una propagación intermitente hacia el resto del tejido auricular cuya frecuencia de activación es más lenta. Aunque las soluciones en el dominio de la tensión y fase para patrones de propagación complejos fueron más suaves y menos precisas, la estimación no invasiva de los mapas de frecuencia fue significativamente más precisa, permitiendo la identificación del gradiente de frecuencia y ubicación de las fuentes de FA de alta frecuencia. Esta técnica puede ser de gran ayuda en la planificación de los procedimientos de ablación, evitando punciones interseptales innecesarias para casos con un gradiente de frecuencia de derecha a izquierda y facilitando la localización de las fuentes de alta frecuencia / [CA] El comportament del cor es regeix per corrents elèctrics generades en el miocardi i, per tant, l'estudi de la seua activitat elèctrica és essencial per al diagnòstic de malalties cardíaques. El problema directe (PD) de l'electrocardiografia implica el càlcul dels potencials del tors a partir de l'activitat elèctrica del cor i el model 3D del cos, mentre que la resolució del problema invers (PI) permet la reconstrucció no invasiva de l'activitat elèctrica del cor a partir de els potencials de superfície. La resolució del PI de l'electrocardiografia té una gran importància en la pràctica clínica atès que fa possible una estimació de l'activitat elèctrica del miocardi únicament a partir de registres no invasius. No obstant això, la resolució del PI segueix sent un gran desafiament per a la electrocardiografia ja que està mal plantejat, és molt inestable i té múltiples solucions. Al llarg d'aquesta tesi s'han desenvolupat diferents estratègies basades en la resolució PI, aplicant-les en el diagnòstic no invasiu d'arítmies ventriculars i auriculars, verificant mitjançant models cel·lulars matemàtics i bases de dades clíniques. La tesi se centra en la resolució del PI per a la reconstrucció no invasiva de l'activitat elèctrica del miocardi per a diferents malalties cardíaques amb diferents patrons de propagació, implementant un nou sistema per a patrons de propagació complexos. A més se han validat els resultats obtinguts i se han classificat els diferents patrons de propagació amb l'estratègia de resolució del PI òptima que minimitze l'error i augmente l'estabilitat del sistema. Un nou mètode iteratiu va ser implementat per a la resolució del PI per fonts dipolars, sent òptim per representar patrons de propagació simples, aconseguint una alta estabilitat i immunitat al soroll en restringir la solució a un nombre limitat de dipols. No obstant això, els patrons de propagació que no poden ser representats per un nombre limitat de dipols s'han de calcular mitjançant la resolució del PI en termes de potencials epicàrdics, proporcionant una estimació més detallada de l'activitat del miocardi. La resolució del PI en el domini de la tensió i fase va mostrar ser molt precís per a patrons de propagació simples i organitzats. Aquest mètode permet el diagnòstic no invasiu de la síndrome de Brugada o la ubicació de focus ectòpics en arítmies auriculars mitjançant una anàlisi paramètric de la morfologia dels electrogrames o la reconstrucció dels mapes d'activació. No obstant això, els resultats matemàtics i clínics presentats en aquesta tesi van demostrar que, per patrons de propagació complexos com la fibril·lació auricular (FA), els resultats obtinguts mitjançant la resolució del PI en el domini de la tensió i fase són massa suaus i optimistes, simplificant enormement la complexitat de la FA, obtenint resultats no fisiològics que no coincideixen amb l'activitat complexa dels electrogrames intracardiacos registrats en pacients amb FA. En aquesta tesi, s'ha proposat una nova tècnica per a la identificació i localització no invasiva de fonts amb una freqüència dominant alta, basat en la suposició que en molts casos les fonts elèctriques que generen i mantenen la FA presenten una taxa d'activació més alta, amb una propagació intermitent cap a la resta del teixit auricular on la freqüència d'activació és més lenta. Encara que, les solucions en el domini de la tensió i fase per patrons de propagació complexos van ser més suaus i menys precises, l'estimació no invasiva dels mapes de freqüència va ser significativament més precisa, permetent la identificació del gradient de freqüència i ubicació de les fonts de FA d'alta freqüència. Aquesta tècnica pot ser de gran ajuda en la planificació dels procediments d'ablació, evitant puncions interseptales innecessaris per a casos amb un gradient de freqüència de dreta a esquerra i facilitant la / Pedrón Torrecilla, J. (2015). Non-invasive Reconstruction of the Myocardial Electrical Activity from Body Surface Potential Recordings [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/58268