L’Analyse isogéométrique (AIG) est une méthode innovante de résolution numérique des équations différentielles, proposée à l’origine par Thomas Hughes, Austin Cottrell et Yuri Bazilevs en 2005. Cette technique de discrétisation est une généralisation de l’analyse par éléments finis classiques (AEF), conçue pour intégrer la conception assistée par ordinateur (CAO), afin de combler l’écart entre la description géométrique et l’analyse des problèmes d’ingénierie. Ceci est réalisé en utilisant des B-splines ou des B-splines rationnelles non uniformes (NURBS), pour la description des géométries ainsi que pour la représentation de champs de solutions inconnus.L’objet de cette thèse est d’étudier la méthode isogéométrique dans le contexte des problèmes hyperboliques en utilisant les fonctions B-splines comme fonctions de base. Nous proposons également une méthode combinant l’AIG avec la méthode de Galerkin discontinue (GD) pour résoudre les problèmes hyperboliques. Plus précisément, la méthodologie de GD est adoptée à travers les interfaces de patches, tandis que l’AIG traditionnelle est utilisée dans chaque patch. Notre méthode tire parti de la méthode de l’AIG et la méthode de GD.Les résultats numériques sont présentés jusqu’à l’ordre polynomial p= 4 à la fois pour une méthode deGalerkin continue et discontinue. Ces résultats numériques sont comparés pour un ensemble de problèmes de complexité croissante en 1D et 2D. / Isogeometric Analysis (IGA) is a modern strategy for numerical solution of partial differential equations, originally proposed by Thomas Hughes, Austin Cottrell and Yuri Bazilevs in 2005. This discretization technique is a generalization of classical finite element analysis (FEA), designed to integrate Computer Aided Design (CAD) and FEA, to close the gap between the geometrical description and the analysis of engineering problems. This is achieved by using B-splines or non-uniform rational B-splines (NURBS), for the description of geometries as well as for the representation of unknown solution fields.The purpose of this thesis is to study isogeometric methods in the context of hyperbolic problems usingB-splines as basis functions. We also propose a method that combines IGA with the discontinuous Galerkin(DG)method for solving hyperbolic problems. More precisely, DG methodology is adopted across the patchinterfaces, while the traditional IGA is employed within each patch. The proposed method takes advantageof both IGA and the DG method.Numerical results are presented up to polynomial order p= 4 both for a continuous and discontinuousGalerkin method. These numerical results are compared for a range of problems of increasing complexity,in 1D and 2D.

大地起伏值為正高與橢球高的差異量，如果取得高精度的大地起伏值，可以利用衛星定位測量施測橢球高並計算得到高精度的正高，其成本低廉，可望取代傳統的水準測量。而大地起伏值可以分為幾何法或重力法的大地起伏值，其中幾何法的大地起伏值計算方法簡易且精度高，可以利用曲面擬合方法取得之。但是幾何法的大地起伏值會受到地形起伏的影響，大範圍的曲面擬合會降低其精度。台灣的地形起伏大，難以進行大範圍曲面擬合。 於是本研究利用環域方法搜尋待測點位鄰近的水準點參與曲面方程式擬合大地起伏，試圖找到最適合的大地起伏擬合範圍。成果顯示：環域的範圍從10公里至30公里，利用二次曲面方程式擬合大地起伏在台灣平地區域能夠達到預測精度與內部精度同時低於5公分。另外由於衛星定位測量橢球高的誤差較高，需進行資料品質評估並進行粗差偵測。針對粗差偵測提出新的方法，利用最佳化演算法中的量子行為粒子群演算法計算最小二乘平差法中的權矩陣，期望能夠將粗差觀測量的權重降低，達到粗差偵測的效果。成果顯示最佳化權矩陣演算法，能夠將粗差對平差系統的影響量降到最低。 本研究建立一套台灣地區的大地起伏擬合作業程序：利用環域搜尋鄰近水準點、曲面方程式及環域範圍選擇與資料的粗差偵測，可獲得高品質的大地起伏。 / The geoidal undulation is the difference of ellipsoid height and orthometric height. We can obtain high accuracy of orthometric height by existing high accuracy of geoidal undulation and the ellipsoidal height measuring by GPS. It expected to replace the traditional leveling survey due to the less cost. This study uses buffer method to search the leveling benchmarks around the object point, attempts to find the proper range of fitting geoidal undulation to curve surface. Experimental results shows that it can archive 5cm level on both prediction error and internal precision by fitting geoidal undulation on 2nd curve surface model where the buffer range is from 10 km to 30 km. In this study, also uses the quantum-behaved particle swarm optimization to calculate the weight matrix of least square adjustment, the purpose is to down-weighting the suspicious outlier, and detect the outlier. Experimental results shows that the optimal weight matrix algorithm can reduce the influence of outlier. This study establish a procedure of fitting geoidal undulation: using buffer analysis to search the adjacent leveling benchmark, selecting the proper buffer range and surface equation and detecting outlier in data.

The point cloud is an unorganized set of points with 3D coordinates (x, y, z) which represents a real object. These point clouds are acquired by the technology called 3D scanning. This scanning technique can be done by various methods, such as LIDAR (Light Detection And Ranging) or by utilizing recently developed 3D scanners. Point clouds can be therefore used in various applications, such as mechanical or reverse engineering, rapid prototyping, biology, nuclear physics or virtual reality. Therefore in this doctoral Ph.D. thesis, I focus on feature detection and visualization in a point cloud. These features represent parts of the object that can be described by the well--known mathematical model (lines, planes, helices etc.). The points on the sharp edges are especialy problematic for commonly used methods. Therefore, I focus on detection of these problematic points. This doctoral Ph.D. thesis presents a new algorithm for precise detection of these problematic points. Visualization of these points is done by a modified curve fitting algoritm with a new weight function that leads to better results. Each of the proposed methods were tested on real data sets and compared with contemporary published methods.

No description available.

This thesis deals with problems of biomechanics of soft tissues, namely of stress-strain analysis of abdominal aortic aneurysm (AAA). The introduction describes briefly the possibility of aneurysm occurrence with a focus on an aneurysm in the abdominal aorta.

Das Finden von zuverlässigen Informationen über gegebene Ereignisse aus großen und dynamischen Textsammlungen, wie dem Web, ist ein wichtiges Thema. Zum Beispiel sind Rettungsteams und Versicherungsunternehmen an prägnanten Fakten über Schäden nach Katastrophen interessiert, die heutzutage online in Web-Blogs, Zeitungsartikeln, Social Media etc. zu finden sind. Solche Fakten helfen, die erforderlichen Hilfsmaßnahmen zu bestimmen und unterstützen deren Koordination. Allerdings ist das Finden, Extrahieren und Aggregieren nützlicher Informationen ein hochkomplexes Unterfangen: Es erfordert die Ermittlung geeigneter Textquellen und deren zeitliche Einordung, die Extraktion relevanter Fakten in diesen Texten und deren Aggregation zu einer verdichteten Sicht auf die Ereignisse, trotz Inkonsistenzen, vagen Angaben und Veränderungen über die Zeit. In dieser Arbeit präsentieren und evaluieren wir Techniken und Lösungen für jedes dieser Probleme, eingebettet in ein vierstufiges Framework. Die angewandten Methoden beruhen auf Verfahren des Musterabgleichs, der Verarbeitung natürlicher Sprache und des maschinellen Lernens. Zusätzlich berichten wir über die Ergebnisse zweier Fallstudien, basierend auf dem Einsatz des gesamten Frameworks: Die Ermittlung von Daten über Erdbeben und Überschwemmungen aus Webdokumenten. Unsere Ergebnisse zeigen, dass es unter bestimmten Umständen möglich ist, automatisch zuverlässige und zeitgerechte Daten aus dem Internet zu erhalten. / Finding reliable information about given events from large and dynamic text collections, such as the web, is a topic of great interest. For instance, rescue teams and insurance companies are interested in concise facts about damages after disasters, which can be found today in web blogs, online newspaper articles, social media, etc. Knowing these facts helps to determine the required scale of relief operations and supports their coordination. However, finding, extracting, and condensing specific facts is a highly complex undertaking: It requires identifying appropriate textual sources and their temporal alignment, recognizing relevant facts within these texts, and aggregating extracted facts into a condensed answer despite inconsistencies, uncertainty, and changes over time. In this thesis, we present and evaluate techniques and solutions for each of these problems, embedded in a four-step framework. Applied methods are pattern matching, natural language processing, and machine learning. We also report the results for two case studies applying our entire framework: gathering data on earthquakes and floods from web documents. Our results show that it is, under certain circumstances, possible to automatically obtain reliable and timely data from the web.

This Master Thesis deals with the study of analytical and finite-element (FE) models for calculation of losses in traction induction motors. Motors are fed through inverters for this type of application. Therefore, both fundamental and harmonic losses are considered. The study is done with one particular motor and one initial analytical model. In order to validate the model and improve it, a FE model is developed with the tool FLUX 2D. Several chosen operating points with different modulation patterns are simulated both with FE and analytical models and results are compared. Stator and rotor Joule losses are studied first. A model to calculate stator Joule losses at strand level is proposed as an improvement to the current analytical model. Then iron losses, both in stator and rotor, are calculated. Two different computations methods with data extraction from FE are studied: the Bertotti model and a recently developed method called MVPRS in the report. It is based on a mathematical model for curve fitting of the core loss material data. Results with the two methods are compared with the ones from ana-lytical model. Finally total fundamental and harmonic losses are compared with measurements and conclusions are drawn on the quality and accuracy of the analytical model. / Detta examensarbete handlar om analytiska och Finita Element (FE) modeller för beräkning av förluster i asynkronmotorer för traktion. Motorer matas genom växelriktare för denna typ av applikation. Därför är det nödvändigt att både grundläggande och harmoniska förluster beaktas. Studien görs för en särskild motor och en redan existerande analytisk modell. För att validera modellen och förbättra den, utvecklats en FE modell med verktyget FLUX 2D. Flera arbetspunkter med olika moduleringsmönster simuleras både med FE och analytiska modeller och resultaten jämförs. Först studeras stator och rotor Joule förluster. En modell för att beräkna stator Joule förluster i varje ledare föreslås som en förbättring av den nuvarande analytiska modellen. Sedan beräknas järnförluster, både i stator och rotor, beräknas. Två olika metoder baserad på flödestäthet variationer i tid och rum från FE simuleringar studeras med Bertottis modell och en nyutvecklad metod som kallas MVPRS. Den är baserat på en matematisk modell för kurvanpassning av materialet förlust data. Resultaten med de två metoderna jämförs med de från analytiska modellen. Slutligen jämförs totala fundamentala och harmoniska förluster med mätningar och slutsatser dras om kvalitet och noggrannhet av analytiska modellen.

This thesis deals with problems of biomechanics of soft tissues, namely of stress-strain analysis of abdominal aortic aneurysm (AAA). The introduction describes briefly the possibility of aneurysm occurrence with a focus on an aneurysm in the abdominal aorta.

No description available.

It is important to know the heat generated due to nuclear decay in the final repository for spent nuclear fuel. In Sweden, the heating powers generated in spent nuclear fuels are currently measured in the calorimeter System 251 at the Clab facility, Oskarshamn. In order to better measure, and increase understanding, of the temperature measurements in the calorimeter, a simple thermodynamic model of its temperature evolution was developed. The model was described as a system of ordinary differential equations, which were solved, and the solution was applied to calibration measurements of the calorimeter. How precise the model is, how its parameters affect the model, et cetera, are addressed. How the temperature evolution of the system changes as the values of parameters in the model are changed is addressed. The mass correction of the calorimeter could be estimated from this model, which validated the established mass correction of the calorimeter. How the measurement results from the calorimeter would be affected if the volume of the calorimeter was changed was also considered. Additionally, gamma radiation escape from the calorimeter without being detected as heat in the calorimeter. The gamma escape energy fraction was estimated by SERPENT simulations of the calorimeter, as a function of the initial photon energy. The gamma escape was also estimated for different values of the radius of System 251.