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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
11

Variational modelling of cavitation and fracture in nonlinear elasticity

Henao Manrique, Duvan Alberto January 2009 (has links)
Motivated by experiments on titanium alloys of Petrinic et al. (2006), which show the formation of cracks through the growth and coalescence of voids in ductile fracture, we consider the problem of formulating a variational model in nonlinear elasticity compatible both with cavitation and the appearance of discontinuities across two-dimensional surfaces. As in the model for cavitation of Müller and Spector (1995) we address this problem, which is connected to the sequential weak continuity of the determinant of the deformation gradient in spaces of functions having low regularity, by means of adding an appropriate surface energy term to the elastic energy. Based upon considerations of invertibility, we derive an expression for the surface energy that admits a physical and a geometrical interpretation, and that allows for the formulation of a model with better analytical properties. We obtain, in particular, important regularity results for the inverses of deformations, as well as the weak continuity of the determinants and the existence of minimizers. We show, further, that the creation of surface can be modeled by carefully analyzing the jump set of the inverses, and we point out some connections between the analysis of cavitation and fracture, the theory of SBV functions, and the theory of Cartesian currents of Giaquinta, Modica, and Soucek. In addition to the above, we extend previous work of Sivaloganathan, Spector and Tilakraj (2006) on the approximation of minimizers for the problem of cavitation with a constraint in the number of flaw points, and present some numerical results for this problem.
12

Matching DSGE models to data with applications to fiscal and robust monetary policy

Kriwoluzky, Alexander 01 December 2009 (has links)
Diese Doktorarbeit untersucht drei Fragestellungen. Erstens, wie die Wirkung von plötzlichen Änderungen exogener Faktoren auf endogene Variablen empirisch im Allgemeinen zu bestimmen ist. Zweitens, welche Effekte eine Erhöhung der Staatsausgaben im Speziellen hat. Drittens, wie optimale Geldpolitik bestimmt werden kann, wenn der Entscheider keine eindeutigen Modelle für die ökonomischen Rahmenbedingungen hat. Im ersten Kapitel entwickele ich eine Methode, mithilfe derer die Effekte von plötzlichen Änderungen exogener Faktoren auf endogene Variablen geschätzt werden können. Dazu wird die gemeinsame Verteilung von Parametern einer Vektor Autoregression (VAR) und eines stochastischen allgemeinen Gleichgewichtsmodelles (DSGE) bestimmt. Auf diese Weise können zentrale Probleme gelöst werden: das Identifikationsproblem der VAR und eine mögliche Misspezifikation des DSGE Modells. Im zweitem Kapitel wende ich die Methode aus dem ersten Kapitel an, um den Effekt einer angekündigten Erhöhung der Staatsausgaben auf den privaten Konsum und die Reallöhne zu untersuchen. Die Identifikation beruht auf der Einsicht, dass endogene Variablen, oft qualitative Unterschiede in der Periode der Ankündigung und nach der Realisation zeigen. Die Ergebnisse zeigen, dass der private Konsum negativ im Zeitraum der Ankündigung reagiert und positiv nach der Realisation. Reallöhne steigen zum Zeitpunkt der Ankündigung und sind positiv für zwei Perioden nach der Realisation. Im abschließendem Kapitel untersuche ich gemeinsam mit Christian Stoltenberg, wie Geldpolitik gesteuert werden sollte, wenn die Modellierung der Ökonomie unsicher ist. Wenn ein Modell um einen Parameter erweitert wird, kann das Modell dadurch so verändert werden, dass sich die Politikempfehlungen zwischen dem ursprünglichen und dem neuen Modell unterscheiden. Oft wird aber lediglich das erweiterte Modell betrachtet. Wir schlagen eine Methode vor, die beiden Modellen Rechnung trägt und somit zu einer besseren Politik führt. / This thesis is concerned with three questions: first, how can the effects macroeconomic policy has on the economy in general be estimated? Second, what are the effects of a pre-announced increase in government expenditures? Third, how should monetary policy be conducted, if the policymaker faces uncertainty about the economic environment. In the first chapter I suggest to estimate the effects of an exogenous disturbance on the economy by considering the parameter distributions of a Vector Autoregression (VAR) model and a Dynamic Stochastic General Equilibrium (DSGE) model jointly. This allows to resolve the major issue a researcher has to deal with when working with a VAR model and a DSGE model: the identification of the VAR model and the potential misspecification of the DSGE model. The second chapter applies the methodology presented in the preceding chapter to investigate the effects of a pre-announced change in government expenditure on private consumption and real wages. The shock is identified by exploiting its pre-announced nature, i.e. different signs of the responses in endogenous variables during the announcement and after the realization of the shock. Private consumption is found to respond negatively during the announcement period and positively after the realization. The reaction of real wages is positive on impact and positive for two quarters after the realization. In the last chapter ''Optimal Policy Under Model Uncertainty: A Structural-Bayesian Estimation Approach'' I investigate jointly with Christian Stoltenberg how policy should optimally be conducted when the policymaker is faced with uncertainty about the economic environment. The standard procedure is to specify a prior over the parameter space ignoring the status of some sub-models. We propose a procedure that ensures that the specified set of sub-models is not discarded too easily. We find that optimal policy based on our procedure leads to welfare gains compared to the standard practice.
13

Diagnostic de panne et analyse des causes profondes du système dynamique inversible / Fault diagnosis & root cause analysis of invertible dynamic system

Zhang, Mei 17 July 2017 (has links)
Beaucoup de services vitaux de la vie quotidienne dépendent de systèmes d'ingénierie hautement complexes et interconnectés; Ces systèmes sont constitués d'un grand nombre de capteurs interconnectés, d'actionneurs et de composants du système. L'étude des systèmes interconnectés joue un rôle important dans l'étude de la fiabilité des systèmes dynamiques; car elle permet d'étudier les propriétés d'un système interconnecté en analysant ses sous-composants moins complexes. Le diagnostic des pannes est essentiel pour assurer des opérations sûres et fiables des systèmes de contrôle interconnectés. Dans toutes les situations, le système global et / ou chaque sous-système peuvent être analysés à différents niveaux pour déterminer la fiabilité du système global. Dans certains cas, il est important de déterminer les informations anormales des variables internes du sous-système local, car ce sont les causes qui contribuent au fonctionnement anormal du processus global. Cette thèse porte sur les défis de l'application de la théorie inverse du système et des techniques FDD basées sur des modèles pour traiter le problème articulaire du diagnostic des fautes et de l'analyse des causes racines (FD et RCA). Nous étudions ensuite le problème de l'inversibilité de la gauche, de l'observabilité et de la diagnosticabilité des fauts du système interconnecté, formant un algorithme FD et RCA multi-niveaux basé sur un modèle. Ce système de diagnostic permet aux composants individuels de surveiller la dynamique interne localement afin d'améliorer l'efficacité du système et de diagnostiquer des ressources de fautes potentielles pour localiser un dysfonctionnement lorsque les performances du système global se dégradent. Par conséquent, un moyen d'une combinaison d'intelligence locale avec une capacité de diagnostic plus avancée pour effectuer des fonctions FDD à différents niveaux du système est fourni. En conséquence, on peut s'attendre à une amélioration de la localisation des fauts et à de meilleurs moyens de maintenance prédictive. La nouvelle structure du système, ainsi que l'algorithme de diagnostic des fautes, met l'accent sur l'importance de la RCA de défaut des dispositifs de terrain, ainsi que sur l'influence de la dynamique interne locale sur la dynamique globale. Les contributions de cette thèse sont les suivantes: Tout d'abord, nous proposons une structure de système non linéaire interconnecté inversible qui garantit le fauts dans le sous-système de périphérique de terrain affecte la sortie mesurée du système global de manière unique et distincte. Une condition nécessaire et suffisante est développée pour assurer l'inversibilité du système interconnecté qui nécessite l'inversibilité de sous-systèmes individuels. Deuxièmement, un observateur interconnecté à deux niveaux est développé; Il se compose de deux estimateurs d'état, vise à fournir des estimations précises des états de chaque sous-système, ainsi que l'interconnexion inconnue. En outre, il fournira également une condition initiale pour le reconstructeur de données et le filtre de fauts local une fois que la procédure FD et RCA est déclenchée par tout fauts. D'une part, la mesure utilisée dans l'estimateur de l'ancien sous-système est supposée non accessible; La solution est de la remplacer par l'estimation fournie par l'estimateur de ce dernier sous-système. / Many of the vital services of everyday life depend on highly complex and interconnected engineering systems; these systems consist of large number of interconnected sensors, actuators and system components. The study of interconnected systems plays a significant role in the study of reliability theory of dynamic systems, as it allows one to investigate the properties of an interconnected system by analyzing its less complicated subcomponents. Fault diagnosis is crucial in achieving safe and reliable operations of interconnected control systems. In all situations, the global system and/or each subsystem can be analyzed at different levels in investigating the reliability of the overall system; where different levels mean from system level down to the subcomponent level. In some cases, it is important to determine the abnormal information of the internal variables of local subsystem, in order to isolate the causes that contribute to the anomalous operation of the overall process. For example, if a certain fault appears in an actuator, the origin of that malfunction can have different causes: zero deviation, leakage, clogging etc. These origins can be represented as root cause of an actuator fault. This thesis concerns with the challenges of applying system inverse theory and model based FDD techniques to handle the joint problem of fault diagnosis & root cause analysis (FD & RCA) locally and performance monitoring globally. By considering actuator as individual dynamic subsystem connected with process dynamic subsystem in cascade, we propose an interconnected nonlinear system structure. We then investigate the problem of left invertibility, fault observability and fault diagnosability of the interconnected system, forming a novel model based multilevel FD & RCA algorithm. This diagnostic algorithm enables individual component to monitor internal dynamics locally to improve plant efficiency and diagnose potential fault resources to locate malfunction when operation performance of global system degrades. Hence, a means of acombination of local intelligence with a more advanceddiagnostic capability (combining fault monitoring anddiagnosis at both local and global levels) to performFDDfunctions on different levels of the plantis provided. As a result, improved fault localization and better predictive maintenance aids can be expected. The new system structure, together with the fault diagnosis algorithm, is the first to emphasize the importance of fault RCA of field devices, as well as the influences of local internal dynamics on the global dynamics. The developed model based multi-level FD & RCA algorithm is then a first effort to combine the strength of the system level model based fault diagnosis with the component level model based fault diagnosis. The contributions of this thesis include the following: Firstly, we propose a left invertible interconnected nonlinear system structure which guarantees that fault occurred in field device subsystem will affect the measured output of the global system uniquely and distinguishably. A necessary and sufficient condition is developed to ensure invertibility of the interconnected system which requires invertibility of individual subsystems. Second, a two level interconnected observer is developed which consists of two state estimators, aims at providing accurately estimates of states of each subsystem, as well as the unknown interconnection. In addition, it will also provide initial condition for the input reconstructor and local fault filter once FD & RCA procedure is triggered by any fault. Two underlyingissues are worth to be highlighted: for one hand, the measurement used in the estimator of the former subsystem is assumed not accessible; the solution is to replace it by the estimate provided by the estimator of the latter subsystem. In fact, this unknown output is the unknown interconnection of the interconnected system, and also the input of the latter subsystem.

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