The particle finite element method (PFEM) in thermo‐mechanical problems

The aim of this work is to develop a numerical framework for accurately and robustly simulating the different conditions exhibited by thermo‐mechanical problems. In particular, the work will focus on the analysis of problems involving large strains, rotations, multiple contacts, large boundary surface changes, and thermal effects. The framework of the numerical scheme is based on the particle finite element method (PFEM) in which the spatial domain is continuously redefined by a distinct nodal reconnection, generated by a Delaunay triangulation. In contrast to classical PFEM calculations, in which the free boundary is obtained by a geometrical procedure (α − shape method), in this work, the boundary is considered as a material surface, and the boundary nodes are removed or inserted by means of an error function. The description of the thermo‐mechanical constitutive model is based on the concepts of large strains plasticity. The plastic flow condition is assumed nearly incompressible, so a u‐p mixed formulation, with a stabilization of the pressure term via the polynomial pressure projection, is proposed. One of the novelties of this work is the use of a combination between the isothermal split and the so‐called IMPL‐EX hybrid integration technique to enhance the robustness and reduce the typical iteration number of the fully implicit Newton–Raphson solution algorithm. The new set of numerical tools implemented in the PFEM algorithm, including new discretization techniques, the use of a projection of the variables between meshes, and the insertion and removal of points allows us to eliminate the negative Jacobians present during large deformation problems, which is one of the drawbacks in the simulation of coupled thermo‐mechanical problems. Finally, two sets of numerical results in 2D are stated. In the first one, the behavior of the proposed locking‐free element type and different time integration schemes for thermo‐mechanical problems is analyzed. The potential of the method for modeling more complex coupled problems as metal cutting and metal forming processes is explored in the last example

Regular Hierarchical Surface Models: A conceptual model of scale variation in a GIS and its application to hydrological geomorphometry

Environmental and geographical process models inevitably involve parameters that vary spatially. One example is hydrological modelling, where parameters derived from the shape of the ground such as flow direction and flow accumulation are used to describe the spatial complexity of drainage networks. One way of handling such parameters is by using a Digital Elevation Model (DEM), such modelling is the basis of the science of geomorphometry. A frequently ignored but inescapable challenge when modellers work with DEMs is the effect of scale and geometry on the model outputs. Many parameters vary with scale as much as they vary with position. Modelling variability with scale is necessary to simplify and generalise surfaces, and desirable to accurately reconcile model components that are measured at different scales. This thesis develops a surface model that is optimised to represent scale in environmental models. A Regular Hierarchical Surface Model (RHSM) is developed that employs a regular tessellation of space and scale that forms a self-similar regular hierarchy, and incorporates Level Of Detail (LOD) ideas from computer graphics. Following convention from systems science, the proposed model is described in its conceptual, mathematical, and computational forms. The RHSM development was informed by a categorisation of Geographical Information Science (GISc) surfaces within a cohesive framework of geometry, structure, interpolation, and data model. The positioning of the RHSM within this broader framework made it easier to adapt algorithms designed for other surface models to conform to the new model. The RHSM has an implicit data model that utilises a variation of Middleton and Sivaswamy (2001)’s intrinsically hierarchical Hexagonal Image Processing referencing system, which is here generalised for rectangular and triangular geometries. The RHSM provides a simple framework to form a pyramid of coarser values in a process characterised as a scaling function. In addition, variable density realisations of the hierarchical representation can be generated by defining an error value and decision rule to select the coarsest appropriate scale for a given region to satisfy the modeller’s intentions. The RHSM is assessed using adaptions of the geomorphometric algorithms flow direction and flow accumulation. The effects of scale and geometry on the anistropy and accuracy of model results are analysed on dispersive and concentrative cones, and Light Detection And Ranging (LiDAR) derived surfaces of the urban area of Dunedin, New Zealand. The RHSM modelling process revealed aspects of the algorithms not obvious within a single geometry, such as, the influence of node geometry on flow direction results, and a conceptual weakness of flow accumulation algorithms on dispersive surfaces that causes asymmetrical results. In addition, comparison of algorithm behaviour between geometries undermined the hypothesis that variance of cell cross section with direction is important for conversion of cell accumulations to point values. The ability to analyse algorithms for scale and geometry and adapt algorithms within a cohesive conceptual framework offers deeper insight into algorithm behaviour than previously achieved. The deconstruction of algorithms into geometry neutral forms and the application of scaling functions are important contributions to the understanding of spatial parameters within GISc

Robust and affordable localization and mapping for 3D reconstruction. Application to architecture and construction

La localización y mapeado simultáneo a partir de una sola cámara en movimiento se conoce como Monocular SLAM. En esta tesis se aborda este problema con cámaras de bajo coste cuyo principal reto consiste en ser robustos al ruido, blurring y otros artefactos que afectan a la imagen. La aproximación al problema es discreta, utilizando solo puntos de la imagen significativos para localizar la cámara y mapear el entorno. La principal contribución es una simplificación del grafo de poses que permite mejorar la precisión en las escenas más habituales, evaluada de forma exhaustiva en 4 datasets. Los resultados del mapeado permiten obtener una reconstrucción 3D de la escena que puede ser utilizada en arquitectura y construcción para Modelar la Información del Edificio (BIM). En la segunda parte de la tesis proponemos incorporar dicha información en un sistema de visualización avanzada usando WebGL que ayude a simplificar la implantación de la metodología BIM.Departamento de Informática (Arquitectura y Tecnología de Computadores, Ciencias de la Computación e Inteligencia Artificial, Lenguajes y Sistemas Informáticos)Doctorado en Informátic

Integrated modelling for 3D GIS

A three dimensional (3D) model facilitates the study of the real world objects it represents. A geoinformation system (GIS) should exploit the 3D model in a digital form as a basis for answering questions pertaining to aspects of the real world. With respect to the earth sciences, different kinds of objects of reality can be realized. These objects are components of the reality under study. At the present state-of-the-art different realizations are usually situated in separate systems or subsystems. This separation results in redundancy and uncertainty when different components sharing some common aspects are combined. Relationships between different kinds of objects, or between components of an object, cannot be represented adequately. This thesis aims at the integration of those components sharing some common aspects in one 3D model. This integration brings related components together, minimizes redundancy and uncertainty. Since the model should permit not only the representation of known aspects of reality, but also the derivation of information from the existing representation, the design of the model is constrained so as to afford these capabilities. The tessellation of space by the network of simplest geometry, the simplicial network, is proposed as a solution. The known aspects of the reality can be embedded in the simplicial network without degrading their quality. The model provides finite spatial units useful for the representation of objects. Relationships between objects can also be expressed through components of these spatial units which at the same time facilitate various computations and the derivation of information implicitly available in the model. Since the simplicial network is based on concepts in geoinformation science and in mathematics, its design can be generalized for n-dimensions. The networks of different dimension are said to be compatible, which enables the incorporation of a simplicial network of a lower dimension into another simplicial network of a higher dimension.The complexity of the 3D model fulfilling the requirements listed calls for a suitable construction method. The thesis presents a simple way to construct the model. The raster technique is used for the formation of the simplicial network embedding the representation of the known aspects of reality as constraints. The prototype implementation in a software package, ISNAP, demonstrates the simplicial network's construction and use. The simplicial network can facilitate spatial and non spatial queries, computations, and 2D and 3D visualizations. The experimental tests using different kinds of data sets show that the simplicial network can be used to represent real world objects in different dimensionalities. Operations traditionally requiring different systems and spatial models can be carried out in one system using one model as a basis. This possibility makes the GIS more powerful and easy to use

A framework for automatic modeling of underground excavations in homogeneous rock mass

Determining the optimum excavation sequence in mining or civil engineering requires using stress analysis methods to repeatedly solve large models. Time consuming preparation of the model and lengthy computations, often measured in days, can have major impacts on successful ongoing operation of an underground mine, where stope failures can cost millions of dollars and perhaps result in closure of the mine. Widespread acceptance of new tunneling methods such as NATM which depend heavily on numerical stress analysis tools and the fact that the effects of excavation at the face of the tunnel are distinctively three dimensional necessitates the use of 3D numerical analysis of these problems. A framework was developed to facilitate efficient modeling of underground excavations and to create an optimal 3D mesh by reducing the number of surface and volume elements while keeping the result of stress analysis accurate enough at the region of interest, where a solution is sought. Fewer surface and volume elements means fewer degrees of freedom in the numerical model. The reduction in number of degrees of freedom directly translates to savings in computational time and resources. The mesh refinement algorithm is driven by a set of criteria that are functions of distance and visibility of points from the region of interest and the framework can be easily extended by adding new types of criteria. A software application was developed to realize the proposed framework and it was applied to a number of mining and civil engineering problems to investigate the applicability, accuracy and efficiency of the framework. The optimized mesh produced by the framework reduced the time to solution significantly and the accuracy of the results obtained from the optimized mesh is comparable to the accuracy of the input data for mining engineering problems

Anisotropic output-based adaptation with tetrahedral cut cells for compressible flows

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2008.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections."September 2008."Includes bibliographical references (leaves 153-164).Anisotropic, adaptive meshing for flows around complex, three-dimensional bodies remains a barrier to increased automation in computational fluid dynamics. Two specific advances are introduced in this thesis. First, a finite-volume discretization for tetrahedral cut-cells is developed that makes possible robust, anisotropic adaptation on complex bodies. Through grid refinement studies on inviscid flows, this cut-cell discretization is shown to produce similar accuracy as boundary-conforming meshes with a small increase in the degrees of freedom. The cut-cell discretization is then combined with output-based error estimation and anisotropic adaptation such that the mesh size and shape are controlled by the output error estimate and the Hessian (i.e. second derivatives) of the Mach number, respectively. Using a parallel implementation, this output-based adaptive method is applied to a series of sonic boom test cases and the automated ability to correctly estimate pressure signatures at several body lengths is demonstrated starting with initial meshes of a few thousand control volumes. Second, a new framework for adaptation is introduced in which error estimates are directly controlled by removing the common intermediate step of specifying a desired mesh size and shape. As a result, output error control can be achieved without the adhoc selection of a specific field (such as Mach number) to control anisotropy, rather anisotropy in the mesh naturally results from both the primal and dual solutions. Furthermore, the direct error control extends naturally to higher-order discretizations for which the use of a Hessian is no longer appropriate to determine mesh shape. The direct error control adaptive method is demonstrated on a series of simple test cases to control interpolation error and discontinuous Galerkin finite element output error. This new direct method produces grids with less elements but the same accuracy as existing metric-based approaches.by Michael Andrew Park.Ph.D

Diversity Within the Master Regulatory p53 Transcriptional Network: Impact of Sequence, Binding Motifs and Mutations

In response to cellular stress and DNA damage, the master regulatory gene p53 directly controls the differential expression of target genes within its extensive transcriptional network through promoter response elements (REs) to elicit many biological responses, including cell cycle arrest and apoptosis. Tetrameric p53 binds the consensus sequence RRRCWWGYYY (n= 0-13) RRRCWWGYYY, where R=purine, W=A/T and Y=pyrimidine. Phenotypic diversity within the p53 transcriptional network occurs as a result of a variety of factors including cell type, post-translational modifications, stress-inducing stimuli, and mutations in p53 that alter transactivation function through changes in the strength of gene activation or spectra of genes regulated. We have developed an isogenomic diploid yeast-based reporter system to evaluate the contribution of target binding sequence, organization and level of p53 on transactivation at target REs by wild-type and mutant p53. The chromosomal position for all of the human derived REs was identical and the number of p53 molecules/cell could be varied over a hundred-fold using an integrated rheostatable GAL1::p53 promoter that is sensitive to level of galactose in the medium. We confirm transactivation by WT p53 differs between REs where small differences in sequence can contribute significantly to levels of transactivation. Through deconstruction of the canonical RE and evaluating transactivation from various sequences and binding motifs, we have challenged the view of what constitutes a functional p53 target. We show small increases in distance between decamer half-sites greatly reduce p53 transactivation. Furthermore, we demonstrate that substantial sequence-dependent transactivation can occur from ½- and ¾-site REs. Importantly, the presence of these noncanonical REs greatly expands the p53 master regulatory network. In addition, we have determined the functional fingerprints of missense mutations to demonstrate that altered function p53 mutations can occur in breast cancers and the transcriptional effects are often subtle. Finally, we have identified super-trans sequences which enhance the efficiency of p53 transactivation by greatly lowering the number of molecules required. These sequences provide a useful tool for addressing wild-type and mutant p53 function. Overall, our findings demonstrate that RE sequence, organization, level of p53 and mutations can strongly impact the ability of the master regulator p53 to transactivate downstream targets, thus diversifying its transcriptional network.Doctor of Philosoph

Decisioning 2022 : Collaboration in knowledge discovery and decision making: Applications to sustainable agriculture

Sustainable agriculture is one of the Sustainable Development Goals (SDG) proposed by UN (United Nations), but little systematic work on Knowledge Discovery and Decision Making has been applied to it. Knowledge discovery and decision making are becoming active research areas in the last years. The era of FAIR (Findable, Accessible, Interoperable, Reusable) data science, in which linked data with a high degree of variety and different degrees of veracity can be easily correlated and put in perspective to have an empirical and scientific perception of best practices in sustainable agricultural domain. This requires combining multiple methods such as elicitation, specification, validation, technologies from semantic web, information retrieval, formal concept analysis, collaborative work, semantic interoperability, ontological matching, specification, smart contracts, and multiple decision making. Decisioning 2022 is the first workshop on Collaboration in knowledge discovery and decision making: Applications to sustainable agriculture. It has been organized by six research teams from France, Argentina, Colombia and Chile, to explore the current frontier of knowledge and applications in different areas related to knowledge discovery and decision making. The format of this workshop aims at the discussion and knowledge exchange between the academy and industry members.Laboratorio de Investigación y Formación en Informática Avanzad

Towards Individualized Transcranial Electric Stimulation Therapy through Computer Simulation

Transkranielle Elektrostimulation (tES) beschreibt eine Gruppe von Hirnstimulationstechniken, die einen schwachen elektrischen Strom über zwei nicht-invasiv am Kopf angebrachten Elektroden applizieren. Handelt es sich dabei um einen Gleichstrom, spricht man von transkranieller Gleichstromstimulation, auch tDCS abgekürzt. Die allgemeine Zielstellung aller Hirnstimulationstechniken ist Hirnfunktion durch ein Verstärken oder Dämpfen von Hirnaktivität zu beeinflussen. Unter den Stimulationstechniken wird die transkranielle Gleichstromstimulation als ein adjuvantes Werkzeug zur Unterstützung der mikroskopischen Reorganisation des Gehirnes in Folge von Lernprozessen und besonders der Rehabilitationstherapie nach einem Schlaganfall untersucht. Aktuelle Herausforderungen dieser Forschung sind eine hohe Variabilität im erreichten Stimulationseffekt zwischen den Probanden sowie ein unvollständiges Verständnis des Zusammenspiels der der Stimulation zugrundeliegenden Mechanismen. Als Schlüsselkomponente für das Verständnis der Stimulationsmechanismen wird das zwischen den Elektroden im Kopf des Probanden aufgebaute elektrische Feld erachtet. Einem grundlegenden Konzept folgend wird angenommen, dass Hirnareale, die einer größeren elektrischen Feldstärke ausgesetzt sind, ebenso einen höheren Stimulationseffekt erfahren. Damit kommt der Positionierung der Elektroden eine entscheidende Rolle für die Stimulation zu. Allerdings verteilt sich das elektrische Feld wegen des heterogenen elektrischen Leitfähigkeitsprofil des menschlichen Kopfes nicht uniform im Gehirn der Probanden. Außerdem ist das Verteilungsmuster auf Grund anatomischer Unterschiede zwischen den Probanden verschieden. Die triviale Abschätzung der Ausbreitung des elektrischen Feldes anhand der bloßen Position der Stimulationselektroden ist daher nicht ausreichend genau für eine zielgerichtete Stimulation. Computerbasierte, biophysikalische Simulationen der transkraniellen Elektrostimulation ermöglichen die individuelle Approximation des Verteilungsmusters des elektrischen Feldes in Probanden basierend auf deren medizinischen Bildgebungsdaten. Sie werden daher zunehmend verwendet, um tDCS-Anwendungen zu planen und verifizieren, und stellen ein wesentliches Hilfswerkzeug auf dem Weg zu individualisierter Schlaganfall-Rehabilitationstherapie dar. Softwaresysteme, die den dahinterstehenden individualisierten Verarbeitungsprozess erleichtern und für ein breites Feld an Forschern zugänglich machen, wurden in den vergangenen Jahren für den Anwendungsfall in gesunden Erwachsenen entwickelt. Jedoch bleibt die Simulation von Patienten mit krankhaftem Hirngewebe und strukturzerstörenden Läsionen eine nicht-triviale Aufgabe. Daher befasst sich das hier vorgestellte Projekt mit dem Aufbau und der praktischen Anwendung eines Arbeitsablaufes zur Simulation transkranieller Elektrostimulation. Dabei stand die Anforderung im Vordergrund medizinische Bildgebungsdaten insbesondere neurologischer Patienten mit krankhaft verändertem Hirngewebe verarbeiten zu können. Der grundlegende Arbeitsablauf zur Simulation wurde zunächst für gesunde Erwachsene entworfen und validiert. Dies umfasste die Zusammenstellung medizinischer Bildverarbeitungsalgorithmen zu einer umfangreichen Verarbeitungskette, um elektrisch relevante Strukturen in den Magnetresonanztomographiebildern des Kopfes und des Oberkörpers der Probanden zu identifizieren und zu extrahieren. Die identifizierten Strukturen mussten in Computermodelle überführt werden und das zugrundeliegende, physikalische Problem der elektrischen Volumenleitung in biologischen Geweben mit Hilfe numerischer Simulation gelöst werden. Im Verlauf des normalen Alterns ist das Gehirn strukturellen Veränderungen unterworfen, unter denen ein Verlust des Hirnvolumens sowie die Ausbildung mikroskopischer Veränderungen seiner Nervenfaserstruktur die Bedeutendsten sind. In einem zweiten Schritt wurde der Arbeitsablauf daher erweitert, um diese Phänomene des normalen Alterns zu berücksichtigen. Die vordergründige Herausforderung in diesem Teilprojekt war die biophysikalische Modellierung der veränderten Hirnmikrostruktur, da die resultierenden Veränderungen im Leitfähigkeitsprofil des Gehirns bisher noch nicht in der Literatur quantifiziert wurden. Die Erweiterung des Simulationsablauf zeichnete sich vorrangig dadurch aus, dass mit unsicheren elektrischen Leitfähigkeitswerten gearbeitet werden konnte. Damit war es möglich den Einfluss der ungenau bestimmbaren elektrischen Leitfähigkeit der verschiedenen biologischen Strukturen des menschlichen Kopfes auf das elektrische Feld zu ermitteln. In einer Simulationsstudie, in der Bilddaten von 88 Probanden einflossen, wurde die Auswirkung der veränderten Hirnfaserstruktur auf das elektrische Feld dann systematisch untersucht. Es wurde festgestellt, dass sich diese Gewebsveränderungen hochgradig lokal und im Allgemeinen gering auswirken. Schließlich wurden in einem dritten Schritt Simulationen für Schlaganfallpatienten durchgeführt. Ihre großen, strukturzerstörenden Läsionen wurden dabei mit einem höheren Detailgrad als in bisherigen Arbeiten modelliert und physikalisch abermals mit unsicheren Leitfähigkeiten gearbeitet, was zu unsicheren elektrischen Feldabschätzungen führte. Es wurden individuell berechnete elektrische Felddaten mit der Hirnaktivierung von 18 Patienten in Verbindung gesetzt, unter Berücksichtigung der inhärenten Unsicherheit in der Bestimmung der elektrischen Felder. Das Ziel war zu ergründen, ob die Hirnstimulation einen positiven Einfluss auf die Hirnaktivität der Patienten im Kontext von Rehabilitationstherapie ausüben und so die Neuorganisierung des Gehirns nach einem Schlaganfall unterstützen kann. Während ein schwacher Zusammenhang hergestellt werden konnte, sind weitere Untersuchungen nötig, um diese Frage abschließend zu klären.:Kurzfassung Abstract Contents 1 Overview 2 Anatomical structures in magnetic resonance images 2 Anatomical structures in magnetic resonance images 2.1 Neuroanatomy 2.2 Magnetic resonance imaging 2.3 Segmentation of MR images 2.4 Image morphology 2.5 Summary 3 Magnetic resonance image processing pipeline 3.1 Introduction to human body modeling 3.2 Description of the processing pipeline 3.3 Intermediate and final outcomes in two subjects 3.4 Discussion, limitations & future work 3.5 Conclusion 4 Numerical simulation of transcranial electric stimulation 4.1 Electrostatic foundations 4.2 Discretization of electrostatic quantities 4.3 The numeric solution process 4.4 Spatial discretization by volume meshing 4.5 Summary 5 Simulation workflow 5.1 Overview of tES simulation pipelines 5.2 My implementation of a tES simulation workflow 5.3 Verification & application examples 5.4 Discussion & Conclusion 6 Transcranial direct current stimulation in the aging brain 6.1 Handling age-related brain changes in tES simulations 6.2 Procedure of the simulation study 6.3 Results of the uncertainty analysis 6.4 Findings, limitations and discussion 7 Transcranial direct current stimulation in stroke patients 7.1 Bridging the gap between simulated electric fields and brain activation in stroke patients 7.2 Methodology for relating simulated electric fields to functional MRI data 7.3 Evaluation of the simulation study and correlation analysis 7.4 Discussion & Conclusion 8 Outlooks for simulations of transcranial electric stimulation List of Figures List of Tables Glossary of Neuroscience Terms Glossary of Technical Terms BibliographyTranscranial electric current stimulation (tES) denotes a group of brain stimulation techniques that apply a weak electric current over two or more non-invasively, head-mounted electrodes. When employing a direct-current, this method is denoted transcranial direct current stimulation (tDCS). The general aim of all tES techniques is the modulation of brain function by an up- or downregulation of brain activity. Among these, transcranial direct current stimulation is investigated as an adjuvant tool to promote processes of the microscopic reorganization of the brain as a consequence of learning and, more specifically, rehabilitation therapy after a stroke. Current challenges of this research are a high variability in the achieved stimulation effects across subjects and an incomplete understanding of the interplay between its underlying mechanisms. A key component to understanding the stimulation mechanism is considered the electric field, which is exerted by the electrodes and distributes in the subjects' heads. A principle concept assumes that brain areas exposed to a higher electric field strength likewise experience a higher stimulation. This attributes the positioning of the electrodes a decisive role for the stimulation. However, the electric field distributes non-uniformly across subjects' brains due to the heterogeneous electrical conductivity profile of the human head. Moreover, the distribution pattern is variable between subjects due to their individual anatomy. A trivial estimation of the distribution of the electric field solely based on the position of the stimulating electrodes is, therefore, not precise enough for a well-targeted stimulation. Computer-based biophysical simulations of transcranial electric stimulation enable the individual approximation of the distribution pattern of the electric field in subjects based on their medical imaging data. They are, thus, increasingly employed for the planning and verification of tDCS applications and constitute an essential tool on the way to individualized stroke rehabilitation therapy. Software pipelines facilitating the underlying individualized processing for a wide range of researchers have been developed for use in healthy adults over the past years, but, to date, the simulation of patients with abnormal brain tissue and structure disrupting lesions remains a non-trivial task. Therefore, the presented project was dedicated to establishing and practically applying a tES simulation workflow. The processing of medical imaging data of neurological patients with abnormal brain tissue was a central requirement in this process. The basic simulation workflow was first designed and validated for the simulation of healthy adults. This comprised compiling medical image processing algorithms into a comprehensive workflow to identify and extract electrically relevant physiological structures of the human head and upper torso from magnetic resonance images. The identified structures had to be converted to computational models. The underlying physical problem of electric volume conduction in biological tissue was solved by means of numeric simulation. Over the course of normal aging, the brain is subjected to structural alterations, among which a loss of brain volume and the development of microscopic alterations of its fiber structure are the most relevant. In a second step, the workflow was, thus, extended to incorporate these phenomena of normal aging. The main challenge in this subproject was the biophysical modeling of the altered brain microstructure as the resulting alterations to the conductivity profile of the brain were so far not quantified in the literature. Therefore, the augmentation of the workflow most notably included the modeling of uncertain electrical properties. With this, the influence of the uncertain electrical conductivity of the biological structures of the human head on the electric field could be assessed. In a simulation study, including imaging data of 88 subjects, the influence of the altered brain fiber structure on the electric field was then systematically investigated. These tissue alterations were found to exhibit a highly localized and generally low impact. Finally, in a third step, tDCS simulations of stroke patients were conducted. Their large, structure-disrupting lesions were modeled in a more detailed manner than in previous stroke simulation studies, and they were physically, again, modeled by uncertain electrical conductivity resulting in uncertain electric field estimates. Individually simulated electric fields were related to the brain activation of 18 patients, considering the inherently uncertain electric field estimations. The goal was to clarify whether the stimulation exerts a positive influence on brain function in the context of rehabilitation therapy supporting brain reorganization following a stroke. While a weak correlation could be established, further investigation will be necessary to answer that research question.:Kurzfassung Abstract Contents 1 Overview 2 Anatomical structures in magnetic resonance images 2 Anatomical structures in magnetic resonance images 2.1 Neuroanatomy 2.2 Magnetic resonance imaging 2.3 Segmentation of MR images 2.4 Image morphology 2.5 Summary 3 Magnetic resonance image processing pipeline 3.1 Introduction to human body modeling 3.2 Description of the processing pipeline 3.3 Intermediate and final outcomes in two subjects 3.4 Discussion, limitations & future work 3.5 Conclusion 4 Numerical simulation of transcranial electric stimulation 4.1 Electrostatic foundations 4.2 Discretization of electrostatic quantities 4.3 The numeric solution process 4.4 Spatial discretization by volume meshing 4.5 Summary 5 Simulation workflow 5.1 Overview of tES simulation pipelines 5.2 My implementation of a tES simulation workflow 5.3 Verification & application examples 5.4 Discussion & Conclusion 6 Transcranial direct current stimulation in the aging brain 6.1 Handling age-related brain changes in tES simulations 6.2 Procedure of the simulation study 6.3 Results of the uncertainty analysis 6.4 Findings, limitations and discussion 7 Transcranial direct current stimulation in stroke patients 7.1 Bridging the gap between simulated electric fields and brain activation in stroke patients 7.2 Methodology for relating simulated electric fields to functional MRI data 7.3 Evaluation of the simulation study and correlation analysis 7.4 Discussion & Conclusion 8 Outlooks for simulations of transcranial electric stimulation List of Figures List of Tables Glossary of Neuroscience Terms Glossary of Technical Terms Bibliograph