Positive approximations of the inverse of fractional powers of SPD M-matrices

This study is motivated by the recent development in the fractional calculus and its applications. During last few years, several different techniques are proposed to localize the nonlocal fractional diffusion operator. They are based on transformation of the original problem to a local elliptic or pseudoparabolic problem, or to an integral representation of the solution, thus increasing the dimension of the computational domain. More recently, an alternative approach aimed at reducing the computational complexity was developed. The linear algebraic system $\cal A^\alpha \bf u=\bf f$, $0< \alpha <1$ is considered, where $\cal A$ is a properly normalized (scalded) symmetric and positive definite matrix obtained from finite element or finite difference approximation of second order elliptic problems in $\Omega\subset\mathbb{R}^d$, $d=1,2,3$. The method is based on best uniform rational approximations (BURA) of the function $t^{\beta-\alpha}$ for $0 < t \le 1$ and natural $\beta$. The maximum principles are among the major qualitative properties of linear elliptic operators/PDEs. In many studies and applications, it is important that such properties are preserved by the selected numerical solution method. In this paper we present and analyze the properties of positive approximations of $\cal A^{-\alpha}$ obtained by the BURA technique. Sufficient conditions for positiveness are proven, complemented by sharp error estimates. The theoretical results are supported by representative numerical tests

Electromagnetic model subdivision and iterative solvers for surface and volume double higher order numerical methods and applications

2019 Fall.Includes bibliographical references.Higher order methods have been established in the numerical analysis of electromagnetic structures decreasing the number of unknowns compared to the low order discretization. In order to decrease memory requirements even further, model subdivision in the computational analysis of electrically large structures has been used. The technique is based on clustering elements and solving/approximating subsystems separately, and it is often implemented in conjunction with iterative solvers. This thesis addresses unique theoretical and implementation details specific to model subdivision of the structures discretized by the Double Higher Order (DHO) elements analyzed by i) Finite Element Method - Mode Matching (FEM-MM) technique for closed-region (waveguide) structures and ii) Surface Integral Equation Method of Moments (SIE-MoM) in combination with (Multi-Level) Fast Multipole Method for open-region bodies. Besides standard application in decreasing the model size, DHO FEM-MM is applied to modeling communication system in tunnels by means of Standard Impedance Boundary Condition (SIBC), and excellent agreement is achieved with measurements performed in Massif Central tunnel. To increase accuracy of the SIE-MoM computation, novel method for numerical evaluation of the 2-D surface integrals in MoM matrix entries has been improved to achieve better accuracy than traditional method. To demonstrate its efficiency and practicality, SIE-MoM technique is applied to analysis of the rain event containing significant percentage of the oscillating drops recorded by 2D video disdrometer. An excellent agreement with previously-obtained radar measurements has been established providing the benefits of accurately modeling precipitation particles

Automatiserad behandlingsplanering inom högintensivt fokuserat ultraljud guidat av magnetresonanstermometri

Högintensivt fokuserat ultraljud guidat av magnetresonanstermometri (MR-HIFU) är en ickeinvasiv medicinsk metod för att åtstadkomma lokal uppvärmning i vävnad, vilket tillämpas främst för behandling av tumörer. Tekniken utnyttjar fokuserat ultraljud för att lokalt höja temperaturen i tumörvävnaden vilket resulterar nekros. För att orsaka ablation i hela tumören krävs det att flera av dessa celler sonikeras. Att manuellt planera hur dessa celler skall placeras, medan behandlingens samtliga säkerhetsaspekter tas i beaktande, är en tidskrävande och monoton process som samtidigt kräver expertis och precision. Dessutom, på grund av behandlingens mångfacetterade karaktär är den svår att optimera manuellt. Syftet med detta arbete var att utforma en algoritm för automatisk behandlingsplanering för MR-HIFU för att förbättra arbetsflödet i planeringsprocessen, samt att producera en prototyp av en dylik algoritm. Den presenterade algoritmen är en stegvis process. Först producerar algoritmen en grupp av positioner som kan sonikeras på ett säkert sätt. Därefter finner algoritmen den optimala undergruppen av dessa positioner. Slutligen optimerar algoritmen resten av de relevanta behandlingsparametrarna. Behandlingen kan optimeras antingen genom att maximera volymen som utsätts för ablation eller genom att minimera tiden som behandlingen kräver. Den presenterade algoritmen är tillräckligt generell för att kunna anpassas till samtliga ablationstillämpningar av MR-HIFU. Den har en modulstruktur vilket förenklar uppgradering, och den kan använda information om hur behandlingen framskrider för att reglera och uppdatera planen. Detta är den första publicerade algoritmen för behandlingsplanering inom MRHIFU som kan optimera behandlingen samt använda återkoppling för att reglera planen. Prototypen testades i två konstgjorda fall samt i ett äkta kliniskt fall vilket dess genomförbarhet.Magnetic Resonance guided High Intensity Focused Ultrasound (MR-HIFU) is a noninvasive medical procedure for localized tissue heating, used mostly in treatment of tumours. The modality utilizes focused ultrasound to raise the temperature of the tumour tissue in small localized volumes, resulting in necrosis. To ablate the whole tumour, several of these sonication cells are need. Planning the positions of the cells, while taking into consideration all safety aspects of the treatment, is a time consuming and monotonous task, but requires at the same time expertise and precision. Furthermore, due to the complex characteristics of a MR-HIFU treatment, it is difficult to optimize manually. The aim of the thesis was to design an outline for an automated treatment planning algorithm for MR-HIFU, and to produce a prototype of such an algorithm. The presented algorithm relies on a step-wise process. First, a set of positions is produced that can be sonicated safely. Then, an optimal subset of those positions is selected. Finally, the remaining treatment parameters are optimized. The treatment can either be optimized for maximum coverage or minimum total treatment time. The proposed algorithm is general enough to be adaptable to all ablation applications of MR-HIFU. It has a modular structure for easy updating, and it is able to improve on the plan during the treatment based on feedback from already delivered cells. This is the first published treatment planning algorithm for MR-HIFU that optimizes the treatment and has the ability to update the plan based on feedback. The prototype was tested in two artificial test cases and one real clinical case, proving its feasibility

Simplex Control Methods for Robust Convergence of Small Unmanned Aircraft Flight Trajectories in the Constrained Urban Environment

Constrained optimal control problems for Small Unmanned Aircraft Systems (SUAS) have long suffered from excessive computation times caused by a combination of constraint modeling techniques, the quality of the initial path solution provided to the optimal control solver, and improperly defining the bounds on system state variables, ultimately preventing implementation into real-time, on-board systems. In this research, a new hybrid approach is examined for real-time path planning of SUAS. During autonomous flight, a SUAS is tasked to traverse from one target region to a second target region while avoiding hard constraints consisting of building structures of an urban environment. Feasible path solutions are determined through highly constrained spaces, investigating narrow corridors, visiting multiple waypoints, and minimizing incursions to keep-out regions. These issues are addressed herein with a new approach by triangulating the search space in two-dimensions, or using a tetrahedron discretization in three-dimensions to define a polygonal search corridor free of constraints while alleviating the dependency of problem specific parameters by translating the problem to barycentric coordinates. Within this connected simplex construct, trajectories are solved using direct orthogonal collocation methods while leveraging navigation mesh techniques developed for fast geometric path planning solutions. To illustrate two-dimensional flight trajectories, sample results are applied to flight through downtown Chicago at an altitude of 600 feet above ground level. The three-dimensional problem is examined for feasibility by applying the methodology to a small scale problem. Computation and objective times are reported to illustrate the design implications for real-time optimal control systems, with results showing 86% reduction in computation time over traditional methods

Biomechanical Modeling and Inverse Problem Based Elasticity Imaging for Prostate Cancer Diagnosis

Early detection of prostate cancer plays an important role in successful prostate cancer treatment. This requires screening the prostate periodically after the age of 50. If screening tests lead to prostate cancer suspicion, prostate needle biopsy is administered which is still considered as the clinical gold standard for prostate cancer diagnosis. Given that needle biopsy is invasive and is associated with issues including discomfort and infection, it is desirable to develop a prostate cancer diagnosis system that has high sensitivity and specificity for early detection with a potential to improve needle biopsy outcome. Given the complexity and variability of prostate cancer pathologies, many research groups have been pursuing multi-parametric imaging approach as no single modality imaging technique has proven to be adequate. While imaging additional tissue properties increases the chance of reliable prostate cancer detection and diagnosis, selecting an additional property needs to be done carefully by considering clinical acceptability and cost. Clinical acceptability entails ease with respect to both operating by the radiologist and patient comfort. In this work, effective tissue biomechanics based diagnostic techniques are proposed for prostate cancer assessment with the aim of early detection and minimizing the numbers of prostate biopsies. The techniques take advantage of the low cost, widely available and well established TRUS imaging method. The proposed techniques include novel elastography methods which were formulated based on an inverse finite element frame work. Conventional finite element analysis is known to have high computational complexity, hence computation time demanding. This renders the proposed elastography methods not suitable for real-time applications. To address this issue, an accelerated finite element method was proposed which proved to be suitable for prostate elasticity reconstruction. In this method, accurate finite element analysis of a large number of prostates undergoing TRUS probe loadings was performed. Geometry input and displacement and stress fields output obtained from the analysis were used to train a neural network mapping function to be used for elastopgraphy imaging of prostate cancer patients. The last part of the research presented in this thesis tackles an issue with the current 3D TRUS prostate needle biopsy. Current 3D TRUS prostate needle biopsy systems require registering preoperative 3D TRUS to intra-operative 2D TRUS images. Such image registration is time-consuming while its real-time implementation is yet to be developed. To bypass this registration step, concept of a robotic system was proposed which can reliably determine the preoperative TRUS probe position relative to the prostate to place at the same position relative to the prostate intra-operatively. For this purpose, a contact pressure feedback system is proposed to ensure similar prostate deformation during 3D and 2D image acquisition in order to bypass the registration step

Scan-based immersed isogeometric analysis

Scan-based simulations contain innate topologically complex three-dimensional geometries, represented by large data sets in formats which are not directly suitable for analysis. Consequently, performing high-fidelity scan-based simulations at practical computational costs is still very challenging. The main objective of this dissertation is to develop an efficient and robust scan-based simulation strategy by acquiring a profound understanding of three prominent challenges in scan-based IGA, viz.: i) balancing the accuracy and computational effort associated with numerical integration; ii) the preservation of topology in the spline-based segmentation procedure; and iii) the control of accuracy using error estimation and adaptivity techniques. In three-dimensional immersed isogeometric simulations, the computational effort associated with integration can be the critical component. A myriad of integration strategies has been proposed over the past years to ameliorate the difficulties associated with integration, but a general optimal integration framework that suits a broad class of engineering problems is not yet available. In this dissertation we provide a thorough investigation of the accuracy and computational effort of the octree integration technique. We quantify the contribution of the integration error using the theoretical basis provided by Strang’s first lemma. Based on this study we propose an error-estimate-based adaptive integration procedure for immersed IGA. To exploit the advantageous properties of IGA in a scan-based setting, it is important to extract a smooth geometry. This can be established by convoluting the voxel data using B-splines, but this can induce problematic topological changes when features with a size similar to that of the voxels are encountered. This dissertation presents a topology-preserving segmentation procedure using truncated hierarchical (TH)B-splines. A moving-window-based topological anomaly detection algorithm is proposed to identify regions in which (TH)B-spline refinements must be performed. The criterion to identify topological anomalies is based on the Euler characteristic, giving it the capability to distinguish between topological and shape changes. A Fourier analysis is presented to explain the effectiveness of the developed procedure. An additional computational challenge in the context of immersed IGA is the construction of optimal approximations using locally refined splines. For scan-based volumetric domains, hierarchical splines are particularly suitable, as they optimally leverage the advantages offered by the availability of a geometrically simple background mesh. Although truncated hierarchical B-splines have been successfully applied in the context of IGA, their application in the immersed setting is largely unexplored. In this dissertation we propose a computational strategy for the application of error estimation-based mesh adaptivity for stabilized immersed IGA. The conducted analyses and developed computational techniques for scan-based immersed IGA are interrelated, and together constitute a significant improvement in the efficiency and robustness of the analysis paradigm. In combination with other state-of-the-art developments regarding immersed FEM/IGA (\emph{e.g.}, iterative solution techniques, parallel computing), the research in this thesis opens the doors to scan-based simulations with more sophisticated physical behavior, geometries of increased complexity, and larger scan-data sizes.Scan-based simulations contain innate topologically complex three-dimensional geometries, represented by large data sets in formats which are not directly suitable for analysis. Consequently, performing high-fidelity scan-based simulations at practical computational costs is still very challenging. The main objective of this dissertation is to develop an efficient and robust scan-based simulation strategy by acquiring a profound understanding of three prominent challenges in scan-based IGA, viz.: i) balancing the accuracy and computational effort associated with numerical integration; ii) the preservation of topology in the spline-based segmentation procedure; and iii) the control of accuracy using error estimation and adaptivity techniques. In three-dimensional immersed isogeometric simulations, the computational effort associated with integration can be the critical component. A myriad of integration strategies has been proposed over the past years to ameliorate the difficulties associated with integration, but a general optimal integration framework that suits a broad class of engineering problems is not yet available. In this dissertation we provide a thorough investigation of the accuracy and computational effort of the octree integration technique. We quantify the contribution of the integration error using the theoretical basis provided by Strang’s first lemma. Based on this study we propose an error-estimate-based adaptive integration procedure for immersed IGA. To exploit the advantageous properties of IGA in a scan-based setting, it is important to extract a smooth geometry. This can be established by convoluting the voxel data using B-splines, but this can induce problematic topological changes when features with a size similar to that of the voxels are encountered. This dissertation presents a topology-preserving segmentation procedure using truncated hierarchical (TH)B-splines. A moving-window-based topological anomaly detection algorithm is proposed to identify regions in which (TH)B-spline refinements must be performed. The criterion to identify topological anomalies is based on the Euler characteristic, giving it the capability to distinguish between topological and shape changes. A Fourier analysis is presented to explain the effectiveness of the developed procedure. An additional computational challenge in the context of immersed IGA is the construction of optimal approximations using locally refined splines. For scan-based volumetric domains, hierarchical splines are particularly suitable, as they optimally leverage the advantages offered by the availability of a geometrically simple background mesh. Although truncated hierarchical B-splines have been successfully applied in the context of IGA, their application in the immersed setting is largely unexplored. In this dissertation we propose a computational strategy for the application of error estimation-based mesh adaptivity for stabilized immersed IGA. The conducted analyses and developed computational techniques for scan-based immersed IGA are interrelated, and together constitute a significant improvement in the efficiency and robustness of the analysis paradigm. In combination with other state-of-the-art developments regarding immersed FEM/IGA (\emph{e.g.}, iterative solution techniques, parallel computing), the research in this thesis opens the doors to scan-based simulations with more sophisticated physical behavior, geometries of increased complexity, and larger scan-data sizes