Tesi sul tema "Towers structure"

The mechanical model usually adopted in the design of transmission lines (TL) latticed steel towers is very simple, using spatial truss and frame elements, and solved by a linear static or non-linear geometric analysis. In the event of rupture of a conductor cable or a shield wire the loading is considered through static equivalent loads , and foundations are usually modeled how undeformable supports. This work evaluated the response of two TL latticed steel towers subjected to the cable rupture, considering the influence of foundation flexibility in the model and type of analysis, i. e., with a dynamic analysis in time domain and a static analysis with the static equivalent loads , usually adopted in design practice. In dynamic analysis, direct explicit numerical integration of the equations of motion in the time domain was adopted, using the central finite differences scheme, and the model included all components of a TL: the towers, the conductor cables, the shield wires, the insulator strings and the foundation elements, in order to evaluate the influence of boundary conditions on the results. Finally, the results of dynamic analysis of towers, in terms of displacements at the top, support reactions and maximum loads in some selected bars are compared with the results of static analysis.
O modelo mecânico usualmente adotado no projeto de torres metálicas treliçadas é bastante simples, utilizando elementos de treliça e/ou pórtico espacial, e resolvido através de uma análise estática e linear ou não linear geométrica. Nas hipóteses de carga de ruptura de um cabo condutor ou um cabo pára-raios o carregamento é considerado através de uma carga estática equivalente , e as fundações geralmente são modeladas com apoios indeslocáveis. Neste trabalho é avaliada a resposta de duas torres metálicas treliçadas de linhas de transmissão (LT) submetidas à hipótese de carga de ruptura de um cabo condutor, considerando a influência da flexibilidade da fundação no modelo e do tipo de análise, isto é, com uma análise dinâmica no domínio do tempo e uma análise estática com as cargas estáticas equivalentes usualmente adotadas na prática de projeto. Na análise dinâmica, o modelo deve contemplar todos os elementos de uma LT, ou seja, as torres, os cabos condutores, os cabos pára-raios e as cadeias de isoladores, a fim de se availar a influência das condições de contorno nos resultados. Por fim, os resultados da análise dinâmica das torres, em termos de deslocamentos no topo e esforços máximos em algumas barras, devem ser comparados com os resultados da análise estática, para que possam ser elaboradas sugestões nos procedimentos de projeto deste tipo de estrutura.

The fluid-structure interaction of reacting materials requires computational models capable of resolving the wide range of scales present in both the condensed phase energetic materials and the turbulent reacting gas phase. This effort is focused on the development of a micro-scale structural model designed to simulate heterogeneous energetic materials used for solid propellants and explosives. These two applications require a model that can track moving surfaces as the material burns, handle spontaneous formation of discontinuities such as cracks, model viscoelastic and viscoplastic materials, include finite-rate kinetics, and resolve both micro-scale features and macro-scale trends. Although a large set of computational models is applied to energetic materials, none meet all of these criteria. The Micro-Scale Dynamical Model serves as the basis for this work. The model is extended to add the capabilities required for energetic materials. Heterogeneous solid propellant burning simulations match experimental burn rate data and descriptions of material surface. Simulations of realistic heterogeneous plastic-bound explosives undergoing impact predict the formation of regions of localized heating called hotspots which may lead to detonation in the material. The location and intensity of these hotspots is found to vary with the material properties of the energetic crystal and binder and with the impact velocity. A statistical model of the hotspot peak temperatures for two frequently used energetic crystals indicates a linear relationship between the hotspot intensity and the impact velocity. This statistical model may be used to generate hotspot fields in macro-scale simulations incapable of resolving the micro-scale heating that occurs in heterogeneous explosives.

In this work we study mixing properties of discrete dynamical systems and related to them geometric structure. In the first chapter we show that the direct product of maps with Young towers admits a Young tower whose return times decay at a rate which is bounded above by the slowest of the rates of decay of the return times of the component maps. An application of this result, together with other results in the literature, yields various statistical properties for the direct product of various classes of systems, including Lorenz-like maps, multimodal maps, piecewise $C^2$ interval maps with critical points and singularities, H\'enon maps and partially hyperbolic systems. The second chapter is dedicated to the problem of decay of correlations for continuous observables. First we show that if the underlying system admits Young tower then the rate of decay of correlations for continuous observables can be estimated in terms of modulus of continuity and the decay rate of tail of Young tower. In the rest of the second chapter we study the relations between the rates of decay of correlations for smooth observables and continuous observables. We show that if the rates of decay of correlations is known for $C^r,$ observables ($r\ge 1$) then it is possible to obtain decay of correlations for continuous observables in terms of modulus of continuity.

Les modèles géologiques sont couramment utilisés pour estimer les ressources souterraines, pour faire des simulations numériques, et pour évaluer les risques naturels ; il est donc important que les modèles géologiques représentent la géométrie des objets géologiques de façon précise. La première étape pour construire un modèle géologique consiste souvent à interpréter des surfaces structurales, telles que les failles et horizons, à partir d'une image sismique ; les objets géologiques identifiés sont ensuite utilisés pour construire le modèle géologique par des méthodes d'interpolation. Les modèles géologiques construits de cette façon héritent donc les incertitudes d'interprétation car une image sismique peut souvent supporter plusieurs interprétations structurales. Dans ce manuscrit, j'étudie le problème de réduire les incertitudes d'interprétation à l'aide des données sismiques. Particulièrement, j'étudie le problème de déterminer, à l'aide des données sismiques, quels modèles sont plus probables que d'autres dans un ensemble des modèles géologiques cohérents. Ce problème sera connu par la suite comme "le problème d'évaluation des modèles géologiques par données sismiques". J'introduis et formalise ce problème. Je propose de le résoudre par génération des données sismiques synthétiques pour chaque interprétation structurale dans un premier temps, ensuite d'utiliser ces données synthétiques pour calculer la fonction-objectif pour chaque interprétation ; cela permet de classer les différentes interprétations structurales. La difficulté majeure d'évaluer les modèles structuraux à l'aide des données sismiques consiste à proposer des fonctions-objectifs adéquates. Je propose un ensemble de conditions qui doivent être satisfaites par la fonction-objectif pour une évaluation réussie des modèles structuraux à l'aide des données sismiques. Ces conditions imposées à la fonction-objectif peuvent, en principe, être satisfaites en utilisant les données sismiques de surface (« surface seismic data »). Cependant, en pratique il reste tout de même difficile de proposer et de calculer des fonctions-objectifs qui satisfassent ces conditions. Je termine le manuscrit en illustrant les difficultés rencontrées en pratique lorsque nous cherchons à évaluer les interprétations structurales à l'aide des données sismiques de surface. Je propose une fonction-objectif générale faite de deux composants principaux : (1) un opérateur de résidus qui calcule les résidus des données, et (2) un opérateur de projection qui projette les résidus de données depuis l'espace de données vers l'espace physique (le sous-sol). Cette fonction-objectif est donc localisée dans l'espace car elle génère des valeurs en fonction de l'espace. Cependant, je ne suis toujours pas en mesure de proposer une implémentation pratique de cette fonction-objectif qui satisfasse les conditions imposées pour une évaluation réussie des interprétations structurales ; cela reste un sujet de recherche
Subsurface structural models are routinely used for resource estimation, numerical simulations, and risk management; it is therefore important that subsurface models represent the geometry of geological objects accurately. The first step in building a subsurface model is usually to interpret structural features, such as faults and horizons, from a seismic image; the identified structural features are then used to build a subsurface model using interpolation methods. Subsurface models built this way therefore inherit interpretation uncertainties since a single seismic image often supports multiple structural interpretations. In this manuscript, I study the problem of reducing interpretation uncertainties using seismic data. In particular, I study the problem of using seismic data to determine which structural models are more likely than others in an ensemble of geologically plausible structural models. I refer to this problem as "appraising structural models using seismic data". I introduce and formalize the problem of appraising structural interpretations using seismic data. I propose to solve the problem by generating synthetic data for each structural interpretation and then to compute misfit values for each interpretation; this allows us to rank the different structural interpretations. The main challenge of appraising structural models using seismic data is to propose appropriate data misfit functions. I derive a set of conditions that have to be satisfied by the data misfit function for a successful appraisal of structural models. I argue that since it is not possible to satisfy these conditions using vertical seismic profile (VSP) data, it is not possible to appraise structural interpretations using VSP data in the most general case. The conditions imposed on the data misfit function can in principle be satisfied for surface seismic data. In practice, however, it remains a challenge to propose and compute data misfit functions that satisfy those conditions. I conclude the manuscript by highlighting practical issues of appraising structural interpretations using surface seismic data. I propose a general data misfit function that is made of two main components: (1) a residual operator that computes data residuals, and (2) a projection operator that projects the data residuals from the data-space into the image-domain. This misfit function is therefore localized in space, as it outputs data misfit values in the image-domain. However, I am still unable to propose a practical implementation of this misfit function that satisfies the conditions imposed for a successful appraisal of structural interpretations; this is a subject for further research

The aim of this research is to calibrate conductive polymer nanocomposite materials for large strain sensing and develop a structural health monitoring algorithm for gossamer structures by using nanocomposites as strain sensors. Any health monitoring system works on the principle of sensing the response (strain, acceleration etc.) of the structure to an external excitation and analyzing the response to find out the location and the extent of the damage in the structure. A sensor network, a mathematical model of the structure, and a damage detection algorithm are necessary components of a structural health monitoring system. In normal operating conditions, a gossamer structure can experience normal strain as high as 50%. But presently available sensors can measure strain up to 10% only, as traditional strain sensor materials do not show low elastic modulus and high electrical conductivity simultaneously. Conductive polymer nanocomposite which can be stretched like rubber (up to 200%) and has high electrical conductivity (sheet resistance 100 Ohm/sq.) can be a possible large strain sensor material. But these materials show hysteresis and relaxation in the variation of electrical properties with mechanical strain. It makes the calibration of these materials difficult. We have carried out experiments on conductive polymer nanocomposite sensors to study the variation of electrical resistance with time dependent strain. Two mathematical models, based on the modified fractional calculus and the Preisach approaches, have been developed to model the variation of electrical resistance with strain in a conductive polymer. After that, a compensator based on a modified Preisach model has been developed. The compensator removes the effect of hysteresis and relaxation from the output (electrical resistance) obtained from the conductive polymer nanocomposite sensor. This helps in calibrating the material for its use in large strain sensing. Efficiency of both the mathematical models and the compensator has been shown by comparison of their results with the experimental data. A prestressed square membrane has been considered as an example structure for structural health monitoring. Finite element analysis using ABAQUS has been carried out to determine the response of the membrane to an uniform transverse dynamic pressure for different damage conditions. A neuro-fuzzy system has been designed to solve the inverse problem of detecting damages in the structure from the strain history sensed at different points of the structure by a sensor that may have a significant hysteresis. Damage feature index vector determined by wavelet analysis of the strain history at different points of the structure are taken by the neuro-fuzzy system as input. The neuro-fuzzy system detects the location and extent of the damage from the damage feature index vector by using some fuzzy rules. Rules associated with the fuzzy system are determined by a neural network training algorithm using a training dataset, containing a set of known input and output (damage feature index vectors, location and extent of damage for different damage conditions). This model is validated by using the sets of input-output other than those which were used to train the neural network.
Ph. D.

Les modèles géologiques sont couramment utilisés pour estimer les ressources souterraines, pour faire des simulations numériques, et pour évaluer les risques naturels ; il est donc important que les modèles géologiques représentent la géométrie des objets géologiques de façon précise. La première étape pour construire un modèle géologique consiste souvent à interpréter des surfaces structurales, telles que les failles et horizons, à partir d'une image sismique ; les objets géologiques identifiés sont ensuite utilisés pour construire le modèle géologique par des méthodes d'interpolation. Les modèles géologiques construits de cette façon héritent donc les incertitudes d'interprétation car une image sismique peut souvent supporter plusieurs interprétations structurales. Dans ce manuscrit, j'étudie le problème de réduire les incertitudes d'interprétation à l'aide des données sismiques. Particulièrement, j'étudie le problème de déterminer, à l'aide des données sismiques, quels modèles sont plus probables que d'autres dans un ensemble des modèles géologiques cohérents. Ce problème sera connu par la suite comme "le problème d'évaluation des modèles géologiques par données sismiques". J'introduis et formalise ce problème. Je propose de le résoudre par génération des données sismiques synthétiques pour chaque interprétation structurale dans un premier temps, ensuite d'utiliser ces données synthétiques pour calculer la fonction-objectif pour chaque interprétation ; cela permet de classer les différentes interprétations structurales. La difficulté majeure d'évaluer les modèles structuraux à l'aide des données sismiques consiste à proposer des fonctions-objectifs adéquates. Je propose un ensemble de conditions qui doivent être satisfaites par la fonction-objectif pour une évaluation réussie des modèles structuraux à l'aide des données sismiques. Ces conditions imposées à la fonction-objectif peuvent, en principe, être satisfaites en utilisant les données sismiques de surface (« surface seismic data »). Cependant, en pratique il reste tout de même difficile de proposer et de calculer des fonctions-objectifs qui satisfassent ces conditions. Je termine le manuscrit en illustrant les difficultés rencontrées en pratique lorsque nous cherchons à évaluer les interprétations structurales à l'aide des données sismiques de surface. Je propose une fonction-objectif générale faite de deux composants principaux : (1) un opérateur de résidus qui calcule les résidus des données, et (2) un opérateur de projection qui projette les résidus de données depuis l'espace de données vers l'espace physique (le sous-sol). Cette fonction-objectif est donc localisée dans l'espace car elle génère des valeurs en fonction de l'espace. Cependant, je ne suis toujours pas en mesure de proposer une implémentation pratique de cette fonction-objectif qui satisfasse les conditions imposées pour une évaluation réussie des interprétations structurales ; cela reste un sujet de recherche
Subsurface structural models are routinely used for resource estimation, numerical simulations, and risk management; it is therefore important that subsurface models represent the geometry of geological objects accurately. The first step in building a subsurface model is usually to interpret structural features, such as faults and horizons, from a seismic image; the identified structural features are then used to build a subsurface model using interpolation methods. Subsurface models built this way therefore inherit interpretation uncertainties since a single seismic image often supports multiple structural interpretations. In this manuscript, I study the problem of reducing interpretation uncertainties using seismic data. In particular, I study the problem of using seismic data to determine which structural models are more likely than others in an ensemble of geologically plausible structural models. I refer to this problem as "appraising structural models using seismic data". I introduce and formalize the problem of appraising structural interpretations using seismic data. I propose to solve the problem by generating synthetic data for each structural interpretation and then to compute misfit values for each interpretation; this allows us to rank the different structural interpretations. The main challenge of appraising structural models using seismic data is to propose appropriate data misfit functions. I derive a set of conditions that have to be satisfied by the data misfit function for a successful appraisal of structural models. I argue that since it is not possible to satisfy these conditions using vertical seismic profile (VSP) data, it is not possible to appraise structural interpretations using VSP data in the most general case. The conditions imposed on the data misfit function can in principle be satisfied for surface seismic data. In practice, however, it remains a challenge to propose and compute data misfit functions that satisfy those conditions. I conclude the manuscript by highlighting practical issues of appraising structural interpretations using surface seismic data. I propose a general data misfit function that is made of two main components: (1) a residual operator that computes data residuals, and (2) a projection operator that projects the data residuals from the data-space into the image-domain. This misfit function is therefore localized in space, as it outputs data misfit values in the image-domain. However, I am still unable to propose a practical implementation of this misfit function that satisfies the conditions imposed for a successful appraisal of structural interpretations; this is a subject for further research

The most common offshore structures are the Jackets which are tools used to extract the oil and natural gas in relative low water depth particularly exist in Adriatic Sea and a lot of them have been constructed in the last 50 years. When the offshore oil and gas resources exhaust, these structures must be replaced to another region containing underground resources or removed if reaching the design life, furthermore, another solution can be considered: changing life of the future working of these platforms by applying renewable energy and alternating them into offshore wind towers. This thesis proposes to study and examine the stiffness matrix of an existing Jacket which consider damaged components for reliability analysis of offshore installations. In this research it was used the 8-step simplified methodology which includes several step to analyze the ability of the offshore jacket structure to examine if it is tolerable to endure the effect of wind or wave loads (environmental forces) more than usual by simulating a minimizing of the stiffness matrix using several random cases which they are ten cases, firstly minimizing in the x direction ( 5 cases) and lastly in y direction and then comparing each of these cases with the original case .It was presented two of the most critical cases to show the effect of each step one in x direction and the other in y direction consequently. At the end it is showed that even the structure jacket is 50 years old it is standable and bearable to face some reduction of its stiffness

In the automobile industry, there is a big push for the automotive car manufacturers to base engineering decisions on the results of Computer Aided Engineering (CAE) solutions, and to transform the prototyping and testing, from a costly iterative process to a final verification and validation step. The variability in components material properties and environmental conditions together with the lack of knowledge about the underlying physics of complex systems often make it impractical to make reliable predictions based on only deterministic CAE models. One such area is the CAE modelling of cast aluminium components. These cast aluminium components have gained a huge relevance in the automobile industries due to their commendable mechanical properties. The advantage of the cast aluminium alloys are being a well-established alloy system in manufacturing processes, their functional integrity and relatively low weight. However, the presence of pores and micro-voids obtained during the manufacturing process constitutes a specific material behaviour and establishes a challenge in modelling of the cast materials. Furthermore, the low ductility of the materialdemands for the advanced numerical model to predict the failure. The main focus of this master thesis work is to investigate modelling technique of a cast aluminium alloy component, a spring tower, for a drop tower test and validate the predicted behaviour with the physical test results. Volvo Car Corporation currently uses a material model provided by MATFEM for cast aluminium parts which are explored in this thesis work, to validate the material model for component level testing. The methodology used to achieve this objective was to develop a boundary condition to perform component level tests in the drop tower and to correlate these with the obtained results found by using various modelling techniques in the explicit solver LS-DYNA. Therefore, precise and realistic modelling of the drop tower is crucial because the simulation results can be influenced by major design changes. A detailed finite element model for the spring tower has been developed from the observations made during the physical testing. The refined model showed good agreement with the existing model for the spring tower and observations from physical tests.

The purpose of this thesis is to create design and static assessment of the viewing tower in western Jeseníky mountains. The Ground plan is formed by regular hexagon with outer diameter 0.8 meter. Glued laminated profiles, steel tubes and elements of solid wood were predominantly used for the construction of the building. The viewing tower has four viewing platforms and total high of the structure is 28.5 meters.

This thesis deals with the design and assessment of the load-bearing structure of the lookout tower. The tower is 37.45 m high with the layout in the shape of a regular octagon. The object is located within the city of Zlín. The project is provisionally drawn in two variants. Hand-static calculation, drawings and engineering report is processed only for one variant. The variants differ in the structure of staircase. The thesis is drawn up pursuant to the standards of ČSN EN.

Le Design computationnel de protéines, en anglais « Computational Protein Design » (CPD), est un champ derecherche récent qui vise à fournir des outils de prédiction pour compléter l'ingénierie des protéines. En effet,outre la compréhension théorique des propriétés physico-chimiques fondamentales et fonctionnelles desprotéines, l’ingénierie des protéines a d’importantes applications dans un large éventail de domaines, y comprisdans la biomédecine, la biotechnologie, la nanobiotechnologie et la conception de composés respectueux del’environnement. Le CPD cherche ainsi à accélérer le design de protéines dotées des propriétés désirées enpermettant le traitement d’espaces de séquences de large taille tout en limitant les coûts financier et humain auniveau expérimental.Pour atteindre cet objectif, le CPD requière trois ingrédients conçus de manière appropriée: 1) une modélisationréaliste du système à remodeler; 2) une définition précise des fonctions objectives permettant de caractériser lafonction biochimique ou la propriété physico-chimique cible; 3) et enfin des méthodes d'optimisation efficacespour gérer de grandes tailles de combinatoire.Dans cette thèse, nous avons abordé le CPD avec une attention particulière portée sur l’optimisationcombinatoire. Dans une première série d'études, nous avons appliqué pour la première fois les méthodesd'optimisation de réseaux de fonctions de coût à la résolution de problèmes de CPD. Nous avons constaté qu’encomparaison des autres méthodes existantes, nos approches apportent une accélération du temps de calcul parplusieurs ordres de grandeur sur un large éventail de cas réels de CPD comprenant le design de la stabilité deprotéines ainsi que de complexes protéine-protéine et protéine-ligand. Un critère pour définir l'espace demutations des résidus a également été introduit afin de biaiser les séquences vers celles attendues par uneévolution naturelle en prenant en compte des propriétés structurales des acides aminés. Les méthodesdéveloppées ont été intégrées dans un logiciel dédié au CPD afin de les rendre plus facilement accessibles à lacommunauté scientifique
Computational Protein Design (CPD) is a very young research field which aims at providing predictive tools to complementprotein engineering. Indeed, in addition to the theoretical understanding of fundamental properties and function of proteins,protein engineering has important applications in a broad range of fields, including biomedical applications, biotechnology,nanobiotechnology and the design of green reagents. CPD seeks at accelerating the design of proteins with wanted propertiesby enabling the exploration of larger sequence space while limiting the financial and human costs at experimental level.To succeed this endeavor, CPD requires three ingredients to be appropriately conceived: 1) a realistic modeling of the designsystem; 2) an accurate definition of objective functions for the target biochemical function or physico-chemical property; 3)and finally an efficient optimization framework to handle large combinatorial sizes.In this thesis, we addressed CPD problems with a special focus on combinatorial optimization. In a first series of studies, weapplied for the first time the Cost Function Network optimization framework to solve CPD problems and found that incomparison to other existing methods, it brings several orders of magnitude speedup on a wide range of real CPD instancesthat include the stability design of proteins, protein-protein and protein-ligand complexes. A tailored criterion to define themutation space of residues was also introduced in order to constrain output sequences to those expected by natural evolutionthrough the integration of some structural properties of amino acids in the protein environment. The developed methods werefinally integrated into a CPD-dedicated software in order to facilitate its accessibility to the scientific community

Este trabajo tiene como meta servir de apoyo a las siguientes generaciones de ingenieros civiles a poder analizar y diseñar torres de celosía con manuales internacionales y propios de nuestro país. Este este trabajo podrás conocer sobre el mundo de las torres eléctricas, las partes que forman, la importancia de su uso, analizar mediante el software SAP2000 y diseñar por tracción y compresión cada uno de sus elementos.
This work aims to support the next generations of civil engineers to be able to analyze and design lattice towers with international manuals and those of our country. In this work, you will be able to learn about the world of electrical towers, the parts they form, the importance of their use, analyze using the SAP2000 software and design each of its elements by traction and compression.
Tesis

Structural dynamics is at the center of wind turbine tower design - excessive vibrations can be caused by a wide range of environmental and mechanical sources and can lead to reduced component life due to fatigue, noise, and impaired public perception of system integrity. Furthermore, periodic turbulent wind conditions can cause system resonance resulting in significantly increased structural loads. Structural vibration issues may become exacerbated in small wind applications where the analytical and experimental resources for system verification and optimization are scarce. This study combines several structural analysis techniques and packages them into a novel and integrated form that can be readily used by the small wind community/designer to gain insight into tower/rotor dynamic interaction, system modal characteristics, and to optimize the design for reduced tower loads and cost. The finite element method is used to model the tower structure and can accommodate various configurations including fixed monopole towers, guy-wire supported towers, and gin-pole and strut supported towers. The turbine rotor is modeled using the Equivalent Hinge-Offset blade model and coupled to the tower structure through the use of Lagrange’s Equations. Standard IEC Aeroelastic load cases are evaluated and transient solutions developed using the Modal Superposition Method and Runge-Kutta 4th order numerical integration. Validation is performed through comparisons to theoretical closed form solutions, physical laboratory test results, and peer studies. Finally a case study is performed by using the tool to simulate the Cal Poly Wind Power Research Center Wind Turbine and Tower System. Included in the case study is an optimization for hypothetical guy-wire placement to minimize tower stresses and maximize the tower’s natural frequency.

Offshore mooring towers are one of a number of single-point mooring (SPM) systems which provide a berthing point for tankers, enabling the transfer of crude oil to or from the moored vessel. The periodic slackening of the mooring hawser between the vessel and the tower gives rise to a discontinuously non-linear restoring function. Hence, the wave-induced motions of the tower can be highly complex, with the possibility of large amplitude, and potentially hazardous motions. A large amount of work has been carried out in studying single-point mooring systems. However, much of this work has focused on mooring forces and tanker motions. Few studies have looked in-depth at the motions of the mooring structure itself. In this thesis, mooring tower motions have been studied in detail using three techniques: numerical analysis, approximate analytical methods, and experimental modelling. Each of these approaches to the problem has demonstrated that large amplitude and hence potentially hazardous motions can occur. Numerical predictions of motion showed very good comparison with measured responses, particularly for synchronous motions. However, for more complex motions, such as subharmonic resonances, the agreement between measured and predicted results was seen to deteriorate. Approximate analytical methods did not perform so well. Useful results were obtained for the simplified single-degree-of-freedom symmetric model only, highlighting the need for a more sophisticated method. This research has been successful in providing insight into the complex non-linear motions of an offshore mooring tower. The fundamental mechanisms and features of the system have been presented. The methodology used in this study has been applied to the specific case of an offshore mooring tower. However, the general approach to investigating the non-linear motions of the structure is widely applicable in the field of offshore engineering.

This work presents mathematical and computational approaches to cover various aspects of metabolic network modelling, especially regarding the limited availability of detailed kinetic knowledge on reaction rates. It is shown that precise mathematical formulations of problems are needed i) to find appropriate and, if possible, efficient algorithms to solve them, and ii) to determine the quality of the found approximate solutions. Furthermore, some means are introduced to gain insights on dynamic properties of metabolic networks either directly from the network structure or by additionally incorporating steady-state information. Finally, an approach to identify key reactions in a metabolic networks is introduced, which helps to develop simple yet useful kinetic models. The rise of novel techniques renders genome sequencing increasingly fast and cheap. In the near future, this will allow to analyze biological networks not only for species but also for individuals. Hence, automatic reconstruction of metabolic networks provides itself as a means for evaluating this huge amount of experimental data. A mathematical formulation as an optimization problem is presented, taking into account existing knowledge and experimental data as well as the probabilistic predictions of various bioinformatical methods. The reconstructed networks are optimized for having large connected components of high accuracy, hence avoiding fragmentation into small isolated subnetworks. The usefulness of this formalism is exemplified on the reconstruction of the sucrose biosynthesis pathway in Chlamydomonas reinhardtii. The problem is shown to be computationally demanding and therefore necessitates efficient approximation algorithms. The problem of minimal nutrient requirements for genome-scale metabolic networks is analyzed. Given a metabolic network and a set of target metabolites, the inverse scope problem has as it objective determining a minimal set of metabolites that have to be provided in order to produce the target metabolites. These target metabolites might stem from experimental measurements and therefore are known to be produced by the metabolic network under study, or are given as the desired end-products of a biotechological application. The inverse scope problem is shown to be computationally hard to solve. However, I assume that the complexity strongly depends on the number of directed cycles within the metabolic network. This might guide the development of efficient approximation algorithms. Assuming mass-action kinetics, chemical reaction network theory (CRNT) allows for eliciting conclusions about multistability directly from the structure of metabolic networks. Although CRNT is based on mass-action kinetics originally, it is shown how to incorporate further reaction schemes by emulating molecular enzyme mechanisms. CRNT is used to compare several models of the Calvin cycle, which differ in size and level of abstraction. Definite results are obtained for small models, but the available set of theorems and algorithms provided by CRNT can not be applied to larger models due to the computational limitations of the currently available implementations of the provided algorithms. Given the stoichiometry of a metabolic network together with steady-state fluxes and concentrations, structural kinetic modelling allows to analyze the dynamic behavior of the metabolic network, even if the explicit rate equations are not known. In particular, this sampling approach is used to study the stabilizing effects of allosteric regulation in a model of human erythrocytes. Furthermore, the reactions of that model can be ranked according to their impact on stability of the steady state. The most important reactions in that respect are identified as hexokinase, phosphofructokinase and pyruvate kinase, which are known to be highly regulated and almost irreversible. Kinetic modelling approaches using standard rate equations are compared and evaluated against reference models for erythrocytes and hepatocytes. The results from this simplified kinetic models can simulate acceptably the temporal behavior for small changes around a given steady state, but fail to capture important characteristics for larger changes. The aforementioned approach to rank reactions according to their influence on stability is used to identify a small number of key reactions. These reactions are modelled in detail, including knowledge about allosteric regulation, while all other reactions were still described by simplified reaction rates. These so-called hybrid models can capture the characteristics of the reference models significantly better than the simplified models alone. The resulting hybrid models might serve as a good starting point for kinetic modelling of genome-scale metabolic networks, as they provide reasonable results in the absence of experimental data, regarding, for instance, allosteric regulations, for a vast majority of enzymatic reactions.
In dieser Arbeit werden mathematische und informatische Ansätze zur Behandlung diverser Probleme im Zusammenhang mit der Modellierung metabolischer Netzwerke vorgestellt, insbesondere unter Berücksichtigung der eingeschränkten Verfügbarkeit detaillierter Enzymkinetiken. Es wird gezeigt, dass präzise mathematische Formulierungen der Probleme notwendig sind, um erstens angemessene und, falls möglich, effiziente Algorithmen zur Lösung zu entwickeln. Und zweitens, um die Güte der so gefundenen Lösungen zu bewerten. Des weiteren werden Methoden zur Analyse dynamischer Eigenschaften metabolischer Netzwerke eingeführt, welche entweder nur auf der Struktur der Netzwerke basieren oder zusätzlich noch Informationen über stationäre Zustände mit berücksichtigen. Außerdem wird eine Strategie zur Bestimmung von Schlüsselreaktionen eines Netzwerkes vorgestellt, welche die Entwicklung kinetischer Modelle vereinfacht. Der Erfolg neuer Technologien ermöglicht eine immer billigere und schnellere Sequenzierung des Genoms. Dies wird in naher Zukunft die Analyse biologischer Netzwerke nicht nur für Spezies, sondern auch für einzelne Individuen ermöglichen. Die automatische Rekonstruktion metabolischer Netzwerke ist bestens dafür geeignet, diese großen Datenmengen auszuwerten. Eine mathematische Formulierung der Rekonstruktion als Optimierungsproblem wird vorgestellt, die sowohl bereits vorhandenes Wissen als auch theoretische Vorhersagen verschiedenster bioinformatischer Methoden berücksichtigt. Die rekonstruierten Netzwerke sind hinsichtlich möglichst großer und plausibler Zusammenhangskomponenten hin optimiert, um fragmentierte und isolierte Teilnetzwerke zu vermeiden. Als Beispiel dient die Rekonstruktion der Saccharosesynthese in Chlamydomonas reinhardtii. Es wird gezeigt, dass das Problem sehr rechenintensiv ist und somit Approximationsalgorithmen erforderlich macht. Das 'inverse scope' Problem hat als Optimierungsziel, für ein gegebenes metabolisches Netzwerk die minimale Menge notwendiger Metabolite zu bestimmen, um eine ebenfalls gegebene Menge von gewünschten Zielmetaboliten zu produzieren. Diese Zielmetabolite können entweder durch experimentellen Messungen festgelegt werden, oder sie sind die gewünschten Endprodukte einer biotechnologischen Anwendung. Es wird gezeigt, dass das 'inverse scope' Problem rechenintensiv ist. Allerdings wird angenommen, dass die Berechnungskomplexität stark von der Anzahl gerichteter Zyklen innerhalb des metabolischen Netzwerkes abhängt. Dies könnte die Entwicklung effizienter Approximationsalgorithmen ermöglichen. Unter der Annahme von Massenwirkungskinetiken erlaubt es die 'chemical reaction network theory' (CRNT), anhand der Struktur metabolischer Netzwerke Rückschlüsse auf Multistabilität zu ziehen. Auch weitere Kinetiken können durch Modellierung von Enzymmechanismen mit berücksichtigt werden. CRNT wird zum Vergleich von mehreren Modellen des Calvinzyklus, welche sich in Größe und Abstraktionsniveau unterscheiden, verwendet. Obwohl für kleinere Modelle Ergebnisse erzielt werden, erlauben es die verfügbaren Theoreme und Algorithmen der CRNT nicht, Aussagen für größere Modelle zu machen, da die gegenwärtigen Implementierungen der Algorithmen an ihre Berechnungsgrenzen stoßen. Sind sowohl die Stoichiometrie eines metabolischen Netzwerkes, als auch die Metabolitkonzentrationen und Flüsse im stationären Zustand bekannt, so kann 'structural kinetic modelling' angewandt werden, um das dynamische Verhalten des Netzwerkes zu analysieren, selbst wenn die expliziten Ratengleichung unbekannt sind. Dieser Ansatz wird verwendet, um den stabilisierenden Einfluss allosterischer Regulation in menschlichen Erythrozyten zu untersuchen. Des weiteren werden die Reaktionen anhand ihrer Bedeutung hinsichtlich Stabilität im stationären Zustand angeordnet. Die wichtigsten Reaktionen bezüglich dieser Ordnung sind Hexokinase, Phosphofructokinase und Pyruvatkinase, welche bekanntermaßen stark reguliert und irreversibel sind. Kinetische Modelle, die auf generischen Ratengleichung beruhen, werden mit detaillierten Referenzmodellen für Erythrozyten und Hepatozyten verglichen. Die generischen Modelle simulieren das Verhalten nur in der Nähe eines gegebenen stationären Zustandes recht gut. Der zuvor erwähnte Ansatz, wichtige Reaktionen bezüglich Stabilität zu identifizieren, wird zur Bestimmung von Schlüsselreaktionen genutzt. Diese Schlüsselreaktionen werden im Detail modelliert, während für alle anderen Reaktionen weiterhin generische Ratengleichung verwendet werden. Die so entstandenen Hybridmodelle können das Verhalten des Referenzmodells signifikant besser beschreiben. Die Hybridmodelle können als Ausgangspunkt zur Erstellung genomweiter kinetischer Modelle dienen.

Multifunctional Structures (MFS) represent one of the most promising disruptive technologies in the space industry. The possibility to merge spacecraft primary and secondary structures as well as attitude control, power management and onboard computing functions is expected to allow for mass, volume and integration effort savings. Additionally, this will bring the modular construction of spacecraft to a whole new level, by making the development and integration of spacecraft modules, or building blocks, leaner, reducing lead times from commissioning to launch from the current 3-6 years down to the order of 10 months, as foreseen by the latest Operationally Responsive Space (ORS) initiatives. Several basic functionalities have been integrated and tested in specimens of various natures over the last two decades. However, a more integrated, system-level approach was yet to be developed. The activity reported in this thesis was focused on the system-level approach to multifunctional structures for spacecraft, namely in the context of nano- and micro-satellites. This thesis documents the work undertaken in the context of the MFS program promoted by the European Space Agency under the Technology Readiness Program (TRP): a feasibility study, including specimens manufacturing and testing. The work sequence covered a state of the art review, with particular attention to traditional modular architectures implemented in ALMASat-1 and ALMASat-EO satellites, and requirements definition, followed by the development of a modular multi-purpose nano-spacecraft concept, and finally by the design, integration and testing of integrated MFS specimens. The approach for the integration of several critical functionalities into nano-spacecraft modules was validated and the overall performance of the system was verified through relevant functional and environmental testing at University of Bologna and University of Southampton laboratories.

South Africa has recently experienced challenges regarding electricity consumption and availability. As part of the country's Integrated Resource Plan, these challenges are to be addressed. This involves a 20 year plan which aims to increase electricity supply capacity as well as reduce the reliance on coal power as part of the global trend to become more environmentally friendly. Wind power, specifically, is to account for a large portion of the renewable energy that is expected to become available by 2030. This results in the need for the understanding of wind turbine design by South African engineers. The dynamic analysis of wind turbine structures, is of particular interest to Civil Engineers. Wind turbine towers are recently of the monopole or tubular type tower, predominantly constructed of either concrete or steel or a combination of both. Steel tubular towers above a height of 80m are generally not recommended for wind turbines owing to cost concerns as well as difficulties in meeting dynamic behaviour requirements. Concrete towers and steel-concrete hybrid towers are recommended for this height regime. The aim of this study was to assess the prospective use of steel tubular towers of varying geometric shape for wind turbines with tower heights of 80m or greater. The study focussed on the analysis of natural frequency and assessing the applicability of steel tubular towers of geometric shapes that have not been previously explored or reported. The turbine of choice for this study was the Vestas V112 3MW type as this is one of the most commonly used and more efficient turbines for towers of this height regime. The results of this study showed that steel monopole towers of heights of 80m and more are still viable options for wind turbine towers. Various geometric tower cases of heights varying from 80m to 120m, produced acceptable fundamental natural frequencies within the allowable frequency range for a Vestas V112 3MW turbine.

Structural topology optimization is a mathematical approach developed to perform design optimization with the purpose of reducing the material usage, while maximizing structural performance, in accordance to specific design constraints. The principles behind this technique have been around for many decades, but recent advancements in the processing power of computers have allowed for the solving of complex problems, such as the optimization of tall wind turbine towers, bridges, and the bracing systems in skyscrapers. There are two approaches commonly used in structural topology optimization: discrete and continuum. This thesis uses continuum topology optimization, which involves adjusting the distribution of a porous elastic solid material to extremize the design objective(s) and to satisfy constraints. The material porosity is the design variable that is adjusted during the optimization process. The design domain is broken down into a system of continuum degenerated finite elements, which are used for both structural analysis and to create a mesh representation of the structural system, just as pixels make up a picture. Solid elements are modeled as having no porosity, while void spaces have total porosity. As the optimization process occurs, the shape of the boundaries, and the number and size of internal holes are altered in order to best meet the design objective(s) and constraint(s). The purpose of performing continuum structural topology optimization of structural elements is to obtain promising concepts which provide a basis upon which to begin the design process. The steps taken in this thesis to optimize the wind turbine tower are: 1. Create a solid model of the tower domain 2. Define the material properties 3. Determine the equivalent static design wind forces using the extreme loading conditions outlined in IEC 61400 4. Formulate the optimization problem by specifying the objective and constraint functions. 5. Solve the optimization problem and interpret the results. This study on continuum topology optimization on the tower shell, indicates even with a significant reduction in material from the original design space, the structure is capable of meeting the design criteria. The results indicate that opening void spaces in the shell of the tower and creating an open lattice shape may be an effective method to reduce the volume of wind turbine towers, as it has in other applications. This concurs with the stated goal of my research, which is to show that topology optimization has the potential to be used in a multitude of practical applications in order to increase efficiency, and reduce cost of the production of wind power.

A big challenge in artificial intelligence (AI) is creating autonomous agents that can interact well with other agents over extended periods of time. Most previously developed algorithms have been designed in the context of Repeated Games, environments in which the agents interact in the same scenario repeatedly. However, in most real-world interactions, relationships between people and autonomous agents consist of sequences of distinct encounters with different incentives and payoff structures. Therefore, in this thesis, we consider Interaction Games, which model interactions in which the scenario changes from encounter to encounter, often in ways that are unanticipated by the players. For example, in Interaction Games, the magnitude of payoffs as well as the structure of these payoffs can differ across encounters. Unfortunately, while there have been many algorithms developed for Repeated Games, there are no known algorithms for playing Interaction Games. Thus, we have developed two different algorithms, augmented Fictitious Play (aFP) and augmented S# (Aug-S#), for playing these games. These algorithms are designed to generalize Fictitious Play and S# algorithms, which were previously created for Repeated Games, to the more general kinds of scenarios modeled by Interaction Games. This thesis primarily focuses on the evaluation of these algorithms. We first analyze the behavioral and performance properties of these algorithms when associating with other autonomous algorithms. We then report on the results of a user study in which these algorithms were paired with people in two different Interaction Games. Our results show that while the generalized algorithms demonstrate many of the same properties in Interaction Games as they do in Repeated Games, the complexity of Interaction Games appear to alter the kinds of behaviors that are successful, particularly in environments in which communication between players is not possible.

Le traitement de la douleur est un domaine d'importance croissante dans la médecine. Pour les douleurs sévères, les opiacés restent parmi les médicaments les plus utilisés, mais ils présent cependant des effets secondaires sérieux, c'est pourquoi les chercheurs continuent à développer de nouveaux analgésiques. Le Tramadol, un opiacé partiel avec un mécanisme particulier, n'induit pas les effets secondaires associés avec la plupart des opiacés. Il a été utilisé durant des années pour le traitement des douleurs modérées et sévères. Cette thèse décrit la synthèse de composés dérivés du Tramadol, ainsi que leur activité biologique. Plus précisément, des dérivés bicycliques possédant les mêmes groupements pharmacophores que le Tramadol ont été synthétisés. Des composés possédant des cycles de taille différente ont été obtenus. Certains dérivés ont été davantage fonctionnalisés en utiliant des réactions d'hydrogénation, de dihydrowylation et d'owygénation. En outre, certains produits ont été soumis à des réactions utilisant l'approche combinatoire. Ainsi, des réactions de type Grignard ont été effectuées avec un robot, dans le but de découvrir, par hasard, des composés intéressants. Les deux approches ont mené à des produits qui possèdent une activité biologique. Ces données biologiques ont été utilisées dans une étude de modélisation moléculaire afin de découvrir de nouvelles cibles. Les expériences de "Docking" sur le récepteur u ont permis d'identifier quelques composés intéressants, malheuresement la synthèse de l'un de ces composés a échoué en raison de problèmes d'hydrolyse d'une fonction cétal. A la fin de ces travaux, une synthèse a été proposée qui permettra vraisemblablement d'obtenir le composé désiré.

Les applications industrielles FSI se caractérisent par des géométries et des matériaux complexes. Afin de prédire avec précision leur comportement, des coûts de calcul élevés sont associés, à la fois en temps et en ressources informatiques. Pour améliorer la qualité de la prédiction sans pénaliser le temps de calcul, et pour réduire le temps de calcul sans impacter la précision disponible aujourd'hui, deux axes principaux sont explorés dans ce travail. Le premier est l'étude d'un algorithme asynchrone qui pourrait permettre l'utilisation de modèles structurels complexes. Le second consiste à étudier la méthode des tranches en combinant l'utilisation d'un modèle RANS et d'un modèle FEM non linéaire. D'une part, l'étude de l'asynchronicité dans le domaine FSI a révélé différents aspect d'intérêt qui doivent être approfondis avant que l'approche puisse être utilisée industriellement. Cependant, un premier traitement des points mentionnés ci-dessus a montré des signe d'amélioration qui pourraient conduire à un algorithme prometteur, qui se situe naturellement entre l'algorithme explicite et l'algorithme implicite. D'autre part, il a été montré que la méthode des tranches développée dans ce travail conduit à une réduction significative du temps de calcul sans dégradation de la précision
FSI industrial applications are often described by complex geometries and materials. In order to accurately predict their behavior, high computational costs are associated, both in time and in computational resources. To improve the quality of the prediction without penalizing the computational time, and to reduce the computational time without impacting the accuracy that is available today, two main axes are explored in this work. The first one is the study of an asynchronous algorithm that could allow the use of complex structural models. The second axis consists of the study of the strip method while combining the use of a RANS model and a non-linear FEM model. On the one hand, the study of asynchronicity in the FSI domain revealed different aspects of interest that must be addressed before the approach can be used industrially. However, a first treatment of the limitations found showed signs of an improvement that could lead to a promising algorithm, one that naturally lies between the implicit external algorithm and the implicit internal algorithm. On the other hand, it was shown that the strip method developed in this work achieves a significant reduction in calculation time while maintaining excellent accuracy

The General Computational Theory of Musical Structure (GCTMS) is a theory that may be employed to obtain a structural description (or set of descriptions) of a musical surface. This theory is independent of any specific musical style of idiom, and can be applied to any musical surface. The musical work is presented to GCTMS as a sequence of discrete symbolically represented musical events (e.g. notes) without higher-level structural elements (e.g. articulation marks, time-signature etc.) - although such information may be used constructively to guide the analytic process. The aim of the application of the theory is to reach a structural description of the musical work that may be considered as 'plausible' or 'permissible' by a human music analyst. As style-dependent knowledge is not embodied in the general theory, highly sophisticated analyses (similar to those an expert analyst may provide) are not expected. The theory gives, however, higher rating to descriptions that may be considered more reasonable or acceptable by human analysts and lower to descriptions that are less plausible. As GCTMS is based on general cognitive and logical principles the analytic descriptions it provides have cognitive relevance at least as far as the output is concerned; this is not necessarily the case for the exact process by which the output is calculated. In this sense the analytic outcome may be said to relate to and may be compared to the intuitive 'understanding' a listener has when repeatedly exposed to a specific musical work. The proposed theory comprises two distinct but closely related stages of development: a) the development of a number of individual components that focus on specialised musical analytical tasks, and b) the development of an elaborate account of how these components relate to and interact with each other so that plausible structural descriptions of a given musical surface may be arrived at.

This thesis investigates the acceleration amplification experienced by solar towers mounted on the rooftops of low-rise industrial buildings during a seismic event. Specifically, this thesis looks to assess the validity of using amplification factors adopted by the ASCE 7-05Minimum Design Loads for Buildings and Other Structures to approximate seismic acceleration amplification for roof-mounted solar towers. To investigate the validity of the ASCE 7-05 amplification factors, this thesis conducts timehistory analyses of three theoretical solar towers mounted on the roof of a case study building. The time history analyses are conducted in the finite element computer modeling program SAP 2000 using 30 historical ground motion records of varying frequency content. Based on the results of the time history analyses, modifications to the ASCE 7-05 provision specific to roof-mounted solar towers are proposed.

This thesis aims at Multi-Objective Optimization under Uncertainty in structural design. We investigate Polynomial Chaos Expansion (PCE) surrogates which require extensive training sets. We then face two issues: high computational costs of an individual Finite Element simulation and its limited precision. From numerical point of view and in order to limit the computational expense of the PCE construction we particularly focus on sparse PCE schemes. We also develop a custom Latin Hypercube Sampling scheme taking into account the finite precision of the simulation. From the modeling point of view,we propose a multifidelity approach involving a hierarchy of models ranging from full scale simulations through reduced order physics up to response surfaces. Finally, we investigate multiobjective optimization of structures under uncertainty. We extend the PCE model of design objectives by taking into account the design variables. We illustrate our work with examples in sheet metal forming and optimal design of truss structures.

This study addresses a tension in contemporary studies of public memory between ideology criticism and postmodern critique. Both strategies of reading public memory rely on a representational logic derived from the assumption that the source for comparison of a memory text occurs in a more fundamental text or event. Drawing heavily from Michel Foucault, the study proposes an alternative to a representational reading strategy based on the concepts of regularity, similitude, articulation, and cultural formation. The reading of Vietnam Veterans Memorial and the Galveston County Vietnam Memorial serves as an example of a non-representational regularity enabled by the cultural formation of pastoral power.

The buckling of compressively-loaded members is one of the most important factors limiting the overall strength and stability of a structure. I have developed novel techniques for using active control to wiggle a structural element in such a way that buckling is prevented. I present the results of analysis, simulation, and experimentation to show that buckling can be prevented through computer-controlled adjustment of dynamical behavior.sI have constructed a small-scale railroad-style truss bridge that contains compressive members that actively resist buckling through the use of piezo-electric actuators. I have also constructed a prototype actively controlled column in which the control forces are applied by tendons, as well as a composite steel column that incorporates piezo-ceramic actuators that are used to counteract buckling. Active control of buckling allows this composite column to support 5.6 times more load than would otherwise be possible.sThese techniques promise to lead to intelligent physical structures that are both stronger and lighter than would otherwise be possible.

Searching for scientific publications is a tedious task, especially when exploring an unfamiliar domain. Typical scholarly search engines produce lengthy unstructured result lists, which are difficult to comprehend, interpret and browse.An informative visual summary could convey useful information about the returned results as a whole, without the need to sift through individual publications.The first contribution of this thesis is a novel method of representing academic search results with concise and informative topic maps. The method consists of two steps: i) extracting interrelated topics from the publication titles and abstracts, and ii) summarizing the resulting topic graph. In the first step we map the returned publications to articles and categories of Wikipedia, constructing a graph of relevant topics with hierarchical relations. In the second step we sequentially build a summary of the topic graph that represents the search results in the most informative way. We rely on sequential prediction to automatically learn to build informative summaries from examples. The summarized topic maps share the most of the benefits and avoid most of the drawbacks of the current methods for grouping documents, such as clustering, topic models, and predefined taxonomies. Specifically, the topic maps are dynamic, fine-grained, of flexible granularity, with up-to-date topics connected with informative relations and having meaningful concise labels. The second contribution of this thesis is a method for bootstrapping domain-specific ontologies from the categories of Wikipedia. The method performs three steps: i) selecting the set of categories relevant to the domain, ii) classifying the categories into classes and individuals, and iii) classifying the sub-category relations into ``subclass-of'', ``instance-of'', ``part-of'' and ``related-to''. In each step we rely on binary classification, which makes the method flexible and easily extensible with new features. For the purpose of academic search, the proposed method advances the creation of semantically rich topic maps. In general, the method semi-automates the construction of large-scale domain ontologies, benefiting multiple potential applications. Providing ground truth data for structured prediction of large objects, such as topic map summaries or domain ontologies, is tedious. The last contribution of this thesis is an initial investigation into reducing the labeling effort in structured prediction tasks. First, we present a labeling interface that suggests topics to be added to the ground truth topic map summary. We modify a state of the art sequential prediction method to iteratively learn from the summaries one topic at a time, while retaining the convergence guarantees. Second, we present an interactive learning method for selecting the categories of Wikipedia relevant to a given domain. The method reduces the number of required labels by actively selecting the queries to the annotator and learning one label at a time.

Searching for scientific publications is a tedious task, especially when exploring an unfamiliar domain. Typical scholarly search engines produce lengthy unstructured result lists, which are difficult to comprehend, interpret and browse.An informative visual summary could convey useful information about the returned results as a whole, without the need to sift through individual publications.The first contribution of this thesis is a novel method of representing academic search results with concise and informative topic maps. The method consists of two steps: i) extracting interrelated topics from the publication titles and abstracts, and ii) summarizing the resulting topic graph. In the first step we map the returned publications to articles and categories of Wikipedia, constructing a graph of relevant topics with hierarchical relations. In the second step we sequentially build a summary of the topic graph that represents the search results in the most informative way. We rely on sequential prediction to automatically learn to build informative summaries from examples. The summarized topic maps share the most of the benefits and avoid most of the drawbacks of the current methods for grouping documents, such as clustering, topic models, and predefined taxonomies. Specifically, the topic maps are dynamic, fine-grained, of flexible granularity, with up-to-date topics connected with informative relations and having meaningful concise labels. The second contribution of this thesis is a method for bootstrapping domain-specific ontologies from the categories of Wikipedia. The method performs three steps: i) selecting the set of categories relevant to the domain, ii) classifying the categories into classes and individuals, and iii) classifying the sub-category relations into ``subclass-of'', ``instance-of'', ``part-of'' and ``related-to''. In each step we rely on binary classification, which makes the method flexible and easily extensible with new features. For the purpose of academic search, the proposed method advances the creation of semantically rich topic maps. In general, the method semi-automates the construction of large-scale domain ontologies, benefiting multiple potential applications. Providing ground truth data for structured prediction of large objects, such as topic map summaries or domain ontologies, is tedious. The last contribution of this thesis is an initial investigation into reducing the labeling effort in structured prediction tasks. First, we present a labeling interface that suggests topics to be added to the ground truth topic map summary. We modify a state of the art sequential prediction method to iteratively learn from the summaries one topic at a time, while retaining the convergence guarantees. Second, we present an interactive learning method for selecting the categories of Wikipedia relevant to a given domain. The method reduces the number of required labels by actively selecting the queries to the annotator and learning one label at a time.

Metallothioneins are a superfamily of small, cysteine-rich, metal-binding proteins, which have been the subject of intense scientific interest since their discovery in the late 1950s. Over the last decade, the advancement of genome sequencing, microarray and high-throughput protein identification techniques has resulted in an exponential increase in the number of plant MT sequences in protein and translated nucleotide databases. These studies show that plant metallothioneins display significant variation in sequence and are discretely expressed during various developmental stages and in different organs. Therefore, it is likely that plant metallothioneins carry out compartmentalised functions for which they possess specific properties. However, there is a relative paucity of academic literature on the structure and biochemical properties of plant MTs and this is a void that needs to be filled before we can establish structure/property and structure/function relationships for these proteins. This research has focussed on a comprehensive characterisation of the solution structure and metal binding dynamics of the wheat Eel/II metallothionein using a range of analytical and biophysical techniques. Mass spectrometry and nuclear magnetic resonance studies have identified six zinc ions in two distinct domains with hitherto unprecedented stoichiometries for MTs: Zn2Cys6 and Zn4CysllHis2. Structure calculations revealed that in addition to these unprecedented stoichiometries, the individual Ee domains possess unique structural features not previously reported in MT literature. In Domain 1, the binding of two zinc ions in a binuclear cluster was observed. When compared to Domain 2, the binuclear cluster displayed remarkable stability towards Wand EDTA attack. In Domain 2 an isolated binding site with stoichiometry ZnCys2His2 was observed, which is proposed to confer a well-defined structure for this domain. However, disruption of this site through mutation or cadmium binding abolishes ordered structure along with the defined binding of six zinc ions. These novel structural features confer distinct backbone and metal dynamic properties in each domain, and are most likely to have a functional significance. A separate avenue of investigation identified a potential role for Ee in zinc donation. A re-examination of previously published literature on the expression levels of Ee mRNA and protein demonstrated that it is conspicuously accumulated during desiccation, which suggests that it is perfectly poised to satisfy the microquota of zinc-dependent sites during rehydration processes. In conclusion, this research has made significant advances in the understanding of the structure/function relationship of the wheat Eel/II metallothionein.

A work develops through methodical inquiry based on the reciprocity inherent in the construction of an object and its evaluation. A physical object informs an initial concept and acts as the fundamental catalyst for subsequent findings. Ordered elements result in the description of a vertical structure. Exploring this structure through a rational and modern approach, the author designs an urban center in the form of a tower. The tower, as a cellular mega-structure, maintains the density and complexity of a city's existing urban fabric. An urbane mega-structure offers a new contribution to humanity through architecture. This proposal establishes a relationship between public spaces, which elevate civic and social life, and private spaces that support individuality. The evaluation of precedent works and the investigation of modern technology support an appropriate solution toward the technical realization of these spaces. The thesis seeks an architecture that augments the tangible, replaces the hopeless and invents the absent.
Master of Architecture

Peptidoglycan glycosyltransferases (PGTs) are highly conserved bacterial enzymes that catalyze the polymerization of the lipidic disaccharide, Lipid II, to form individual peptidoglycan (PG) strands which are subsequently cross-linked to form mature PG, the major skeletal component of the bacterial cell wall. Recent advances in the preparation of well-defined PGT substrates have enabled the biochemical characterization of Lipid II polymerization by the PGTs. In the course of these studies, we have observed that a distinctive lag phase in the initial rate of PG synthesis by the PGTs can be abrogated if the enzyme is preincubated with Lipid IV, the shortest PG fragment. The origins of this lag phase are intriguing because the chemical transformation involved in coupling Lipid II to yield Lipid IV is identical to the transformation involved in the synthesis of longer PG fragments from Lipid II. Crystallographic structures of the PGTs with Moenomycin A, an inhibitor that is believed to bind to the same site as Lipid IV, suggest that the PGTs possess flexible regions near the putative active site that can undergo substrate-induced conformational changes to accelerate PG synthesis. However, there is currently no structural evidence on how the PGTs interact with its substrates. The work in this thesis lays the foundation for pursuing a solution structure of a Lipid IV bound PGT complex by Nuclear Magnetic Resonance (NMR) spectroscopy, enabling the study of important enzyme conformational states and structural dynamics involved in PG synthesis. Specifically, Chapter 2 of this thesis presents the biochemical evidence that the preincubation of the PGTs with a Lipid IV derivative, Gal-Lipid IV abrogates the lag phase and accelerates the initial rate of PG synthesis. Chapter 3 presents a robust methodology for obtaining multimilligram quantities of isotope labeled, monodisperse and monomeric SgtB, a PGT from a clinically relevant pathogen, Staphylococcus aureus for solution structural studies. Chapter 4 describes the systematic development of a methodology for producing a well-behaved, stable sample of Moenomycin A bound SgtB for NMR spectroscopy. Chapter 5 delineates the adaptation of the methodology described in Chapter 4 for pursuing the solution structure of Lipid IV bound SgtB.
Chemistry and Chemical Biology

Nous étudions dans cette thèse le problème de reconstruction 3D multi-vue à partir d’une séquence d’images au sol acquises dans des environnements urbains ainsi que la prise en compte d’a priori permettant la préservation de la structure sous-jacente de la géométrie 3D observée, ainsi que le passage à l’échelle de tels processus de reconstruction qui est intrinsèquement délicat dans le contexte de l’imagerie urbaine. Bien que ces deux axes aient été traités de manière extensive dans la littérature, les méthodes de reconstruction 3D structurée souffrent d’une complexité en temps de calculs restreignant significativement leur intérêt. D’autre part, les approches de reconstruction 3D large échelle produisent généralement une géométrie simplifiée, perdant ainsi des éléments de structures qui sont importants dans le contexte urbain. L’objectif de cette thèse est de concilier les avantages des approches de reconstruction 3D structurée à celles des méthodes rapides produisant une géométrie simplifiée. Pour ce faire, nous présentons “Patchwork Stereo”, un framework qui combine stéréoscopie photométrique utilisant une poignée d’images issues de points de vue éloignés, et un nuage de point épars. Notre méthode intègre une analyse simultanée 2D-3D réalisant une extraction robuste de plans 3D ainsi qu’une segmentation d’images top-down structurée et repose sur une optimisation par champs de Markov aléatoires. Les contributions présentées sont évaluées via des expériences quantitatives et qualitatives sur des données d’imagerie urbaine complexes illustrant des performances tant quant à la fidélité structurelle des reconstructions 3D que du passage à l’échelle
In this thesis, we address the problem of 3D reconstruction from a sequence of calibrated street-level photographs with a simultaneous focus on scalability and the use of structure priors in Multi-View Stereo (MVS).While both aspects have been studied broadly, existing scalable MVS approaches do not handle well the ubiquitous structural regularities, yet simple, of man-made environments. On the other hand, structure-aware 3D reconstruction methods are slow and scale poorly with the size of the input sequences and/or may even require additional restrictive information. The goal of this thesis is to reconcile scalability and structure awareness within common MVS grounds using soft, generic priors which encourage : (i) piecewise planarity, (ii) alignment of objects boundaries with image gradients and (iii) with vanishing directions (VDs), and (iv) objects co-planarity. To do so, we present the novel “Patchwork Stereo” framework which integrates photometric stereo from a handful of wide-baseline views and a sparse 3D point cloud combining robust 3D plane extraction and top-down image partitioning from a unified 2D-3D analysis in a principled Markov Random Field energy minimization. We evaluate our contributions quantitatively and qualitatively on challenging urban datasets and illustrate results which are at least on par with state-of-the-art methods in terms of geometric structure, but achieved in several orders of magnitude faster paving the way for photo-realistic city-scale modeling

This dissertation is a defense of a particular theory of the metaphysics of time which I call "accretivism", but which is popularly known in a form usually called the "Growing Block Theory". The goal of a metaphysics of time is to incorporate the various aspects of our temporal experience into a single, comprehensive whole. To this end I delineate five aspects of our ordinary experience of time: 1) The Tensed Aspect, in virtue of which objects are presented to us as past, present, or future; 2) The Transitory Aspect, in virtue of which time passes or "flows"; 3) The Durational Aspect, in virtue of which entities have a certain temporal extent; 4) The Structural Aspect, in virtue of which entities are given as being in temporal relations to one another, and 5) The Differential-Repetitive Aspect, in virtue of which things are different from one time to another, and yet there is a certain recurrence of aspects of our experience form one time to another. I contrast the accretivist picture of time, according to which that which is past and that which is present both have ontological status, but nothing which is future has ontological status, and in which temporal passage consists in the coming-into-being of new entities at the temporal edge of reality marked by the present, with the two dominant theories of time in the contemporary literature: 1) presentism, according to which only that which is present has ontological status, and 2) four-dimensionalism, according to which time is to be understood on analogy with spatial dimensions. Accretivism, I argue, is superior to the other two views in virtue of the fact that it gives full status to both the Structural Aspect of Time, for which the presentist has difficulty accounting, and the Transitory Aspect of Time, for which the four-dimensionalist has difficulty accounting. I then defend the accretivist picture against a variety of objections that might be raised to it.

Human vision is our most important sensory system, allowing us to perceive our surroundings. It is an extremely complex process that starts with light entering the eye and ends inside of the brain, with most of its mechanisms still to be explained. When we observe a scene, the optics of the eye focus an image on the retina, where light signals are processed and sent all the way to the visual cortex of the brain, enabling our visual sensation. The progress of retinal research, especially on the topography of photoreceptors, is often tied to the progress of retinal imaging systems. The latest adaptive optics techniques have been essential for the study of the photoreceptors and their spatial characteristics, leading to discoveries that challenge the existing theories on color sensation. The organization of the retina is associated with various perceptive phenomena, some of them are straightforward and strictly related to visual performance like visual acuity or contrast sensitivity, but some of them are more difficult to analyze and test and can be related to the submosaics of the three classes of cone photoreceptors, like how the huge interpersonal differences between the ratio of different cone classes result in negligible differences in color sensation, suggesting the presence of compensation mechanisms in some stage of the visual system. In this dissertation will be discussed and addressed issues regarding the spatial organization of the photoreceptors in the human retina. A computational model has been developed, organized into a modular pipeline of extensible methods each simulating a different stage of visual processing. It does so by creating a model of spatial distribution of cones inside of a retina, then applying descriptive statistics for each photoreceptor to contribute to the creation of a graphical representation, based on a behavioral model that determines the absorption of photoreceptors. These apparent color stimuli are reconstructed in a representation of the observed scene. The model allows the testing of different parameters regulating the photoreceptor's topography, in order to formulate hypothesis on the perceptual differences arising from variations in spatial organization.