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In this age, there are many applications of inverse problems to lots of areas ranging from astronomy, geoscience and so on. For example, image reconstruction and deblurring require the use of methods to solve inverse problems. Since the problems are subject to many factors and noise, we can't simply apply general inversion methods. Furthermore in the problems of interest, the number of unknown variables is huge, and some may depend nonlinearly on the data, such that we must solve nonlinear problems. It is quite different and significantly more challenging to solve nonlinear problems than linear inverse problems, and we need to use more sophisticated methods to solve these kinds of problems. / Master of Science / In various research areas, there are many required measurements which can't be observed due to physical and economical reasons. Instead, these unknown measurements can be recovered by known measurements. This phenomenon can be modeled and be solved by mathematics.

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

京都大学 / 新制・課程博士 / 博士(人間・環境学) / 甲第25365号 / 人博第1107号 / 新制||人||259(附属図書館) / 京都大学大学院人間・環境学研究科共生人間学専攻 / (主査)教授 足立 匡義, 教授 上木 直昌, 教授 角 大輝, 教授 峯 拓矢 / 学位規則第4条第1項該当 / Doctor of Human and Environmental Studies / Kyoto University / DFAM

Data assimilation arises in a vast array of different topics: traditionally in meteorological and oceanographic modelling, wind tunnel or water tunnel experiments and recently from biomedical engineering. Data assimilation is a process for combine measured or observed data with a mathematical model, to obtain estimates of the expected data. The measured data usually contains inaccuracies and is given with low spatial and/or temporal resolution. In this thesis data assimilation for time dependent fluid flow is considered. The flow is assumed to satisfy a given partial differential equation, representing the mathematical model. The problem is to determine the initial state which leads to a flow field which satisfies the flow equation and is close to the given data. In the first part we consider one-dimensional flow governed by Burgers’ equation. We analyze two iterative methods for data assimilation problem for this equation. One of them so called adjoint optimization method, is based on minimization in L2-norm. We show that this minimization problem is ill-posed but the adjoint optimization iterative method is regularizing, and represents the well-known Landweber method in inverse problems. The second method is based on L2-minimization of the gradient. We prove that this problem always has a solution. We present numerical comparisons of these two methods. In the second part three-dimensional inviscid compressible flow represented by the Euler equations is considered. Adjoint technique is used to obtain an explicit formula for the gradient to the optimization problem. The gradient is used in combination with a quasi-Newton method to obtain a solution. The main focus regards the derivation of the adjoint equations with boundary conditions. An existing flow solver EDGE has been modified to solve the adjoint Euler equations and the gradient computations are validated numerically. The proposed iteration method are applied to a test problem where the initial pressure state is reconstructed, for exact data as well as when disturbances in data are present. The numerical convergence and the result are satisfying.

Bed topography identification in open channel and glacier flows is of paramount importance for the study of the respective flows. In the former, the knowledge of the channel bed topography is required for modelling the hydrodynamics of open channel flows, fluvial hydraulics, flood propagation, and river flow monitoring. Indeed, flow models based on the Shallow Water Approximation require prior information on the channel bed topography to accurately capture the flow features. While in the latter, usable bedrock topographic information is very important for glacier flow modellers to accurately predict the flow characteristics. Experimental techniques to infer the bed topography are usually used but are mostly time consuming, costly, and sometimes not possible due to geographical restrictions. However, the measurement of free surface elevation is relatively easy. Alternative to experimental techniques, it is therefore important to develop fast, easy-to-implement, and cost-effective numerical methods. The inverse of the classical hydrodynamic problem corresponds to the determination of hydraulic parameters from measurable quantities. The forward problem uses model parameters to determine measurable quantities. New one-shot and direct pseudo-analytical and numerical approaches for reconstructing the channel bed topography from known free surface elevation data is developed for one-dimensional shallow water flows. It is shown in this work that instead of treating this inverse problem in the traditional partial differential equation (PDE)-constrained optimization framework, the governing equations of the direct problem can be conveniently rearranged to obtain an explicit PDE for the inverse problem. This leads to a direct solution of the inverse problem which is successfully tested on a range of benchmark problems and experimental data for noisy and noiseless free surface data. It was found that this solution approach creates very little amplification of noise. A numerical technique which uses the measured free surface velocity to infer the channel bed topography is also developed. The one-dimensional shallow water equations along with an empirical relationship between the free surface and the depth averaged velocities are used for the inverse problem analysis. It is shown that after a series of algebraic manipulation and integration, the equation governing the inverse problem simplifies to a simple integral equation. The proposed method is tested on a range of analytical and experimental benchmark test cases and the results confirm that, it is possible to reconstruct the channel bed topography from a known free surface velocity distribution of one-dimensional open channel flows. Following the analysis of the case of one-dimensional shallow water flows, a numerical technique for reconstructing the channel bed topography from known free surface elevation data for steep open channel flows is developed using a modified set of equations for which the zero-inertia shallow water approximation holds. In this context, the shallow water equations are modified by neglecting inertia terms while retaining the effects of the bed slope and friction terms. The governing equations are recast into a single first-order partial differential equation which describes the inverse problem. Interestingly, the analysis shows that the inverse problem does not require the knowledge of the bed roughness. The forward problem is solved using MacCormack’s explicit numerical scheme by considering unsteady modified shallow water equations. However, the inverse problem is solved using the method of characteristics. The results of the inverse and the forward problem are successfully tested against each other. In the framework of full two-dimensional shallow water equations, an easy-to-implement and fast to solve direct numerical technique is developed to solve the inverse problem of shallow open channel flows. The main underlying idea is analogous to the idea implemented for the case of one-dimensional reconstruction. The technique described is a “one-shot technique” in the sense that the solution of the partial differential equation provides the solution to the inverse problem directly. The idea is tested on a set of artificial data obtained by first solving the forward problem. Glaciers are very important as an indicator of future climate change or to trace past climate. They respond quickly compared to the Antarctica and Greenland ice sheets which make them ideal to predict climate changes. Glacier bedrock topography is an important parameter in glacier flow modelling to accurately capture its flow dynamics. Thus, a mathematical technique to infer this parameter from measured free surface data is invaluable. Analogous to the approaches implemented for open channel flows, easy-to-implement direct numerical and analytical algorithms are developed to infer the bedrock topography from the knowledge of the free surface elevation in one space dimension. The numerical and analytical methods are both based on the Shallow Ice Approximation and require the time series of the ablation/accumulation rate distribution. Moreover, the analytical method requires the knowledge of a non-zero glacier thickness at an arbitrary location. Numerical benchmark test cases are used to verify the suitability and applicability of the algorithms.

L’amélioration des images sismiques peut aider à mieux contraindre l’exploration deshydrocarbures. Les ondes élastiques qui se propagent dans la Terre peuvent être classifiéescomme ondes de volume et ondes de surface. Si ces dernières sont les plus énergétiques,seules les ondes de volume sont couramment considérées comme des signaux utiles.Cependant, les ondes de surface sont utiles pour caractériser la proche sub-surface.Classiquement, les ondes de surface sont analysées dans des contextes de propriétésélastiques localement 1D.Nous proposons une modification de l’inversion des formes d’onde classique pourreconstruire des profils de propriétés 2D (la windowed-Amplitude Waveform Inversion, w-AWI). La w-AWI est spécialement robuste en ce qui concerne le choix du modèle initial.Nous appliquons la w-AWI aux données synthétiques ainsi qu’aux données réelles, montrantque cette approche permet de récupérer des propriétés 2D. / High-resolution seismic imaging is essential to improve results of hydrocarbon exploration.Elastic waves propagate in the Earth as body and surface waves, the latter being the mostenergetic ones. Body waves are preferred for exploration seismic imaging while surfacewaves are usually considered to be noise. However, it has been recognised that the nearsurface can be characterised by analysing surface waves and that such result may improvethe outcome of body-wave processing. Currently, surface waves analysis leads to retrievelocal 1D property profiles.We propose a waveform-based inversion procedure to derive 2D velocity models fromsurface waves. This method consists of a misfit functional modification of classical FullWaveform Inversion and we call it windowed-Amplitude Waveform Inversion (w-AWI). Weshow that w-AWI is robust regarding the choice of initial velocity model. We apply w-AWI tosynthetic and real data obtaining encouraging near-surface imaging results