In the thesis lubrication and wear at metal/HDPE contacts was addressed. In particular this type of contact occurs in artificial joint replacements. Wear of HDPE was recognized as a major factor limiting device performance. In the thesis, fully implicit fully coupled numerical approach was developed to simulate lubrication and wear. Approach allows solving stationary and transient problems for rough surfaces in a wide range of parameters. Wear coefficients were estimated from experimental data. Wear particles formed in wear process were investigated. Particles were found to be approximately 100 nm in diameter and spherical in shape. Considering theoretical solutions, it was concluded that debris may play a role of third-body abrasive wear particles. In the summary section, some discussion was provided on the topic of theoretical modeling of friction and wear and recommendations for future research were formulated.

Title: Nucleation in complex systems Author: Jan Kulveit Institute: Institute of Physics of the Czech Academy of Sciences Supervisor: prof. Pavel Demo, Institute of Physics of the Czech Academy ofSciences, Department of Optical Materials Abstract: We studied nucleation in progressively more abstract contexts and systems, starting from classical nucleation theory and ending with nucleation in complex networks. The cases studied include impurity nucleation in a solid matrix on several alkali halide crystals, where we determined formation energies for clusters, treated as defects, starting from single impurity-vacancy dipole and small aggregates to possible configurations of larger clusters. In the next part, we turn to the study of heterogeneous nucleation. While in the usual treatment of heterogeneous nucleation the surface energy is assumed to be homogenous, we ask the question what happens if we consider the surface energy to be heteroge- neous.Utilizing umbrella sampling computer simulations we find the nucleation barrier can be significantly lowered in the presence of surface heterogeneity, even if the average surface energy is kept constant. In the last part we study influence of clustering coefficient on phase transitions in scale-free networks, using forward flux sampling (FFS). Keywords: nucleation,...

Matěj Malecha, Akcident ve Stacku Abstract (in English): The master thesis explains the notion of "accident" in the book The Stack: On Software and Sovereignty by Benjamin H. Bratton. First, it identifies suitable mental models within the fields of complex systems theory, philosophy of technology and theory of information. The models inform subsequent analysis and interpretation of the Stack showing that Stack's accidentality (1) is an inevitable consequence of the functional principle of digital technologies, and that (2) the accidentality differs qualitatively depending on whether it manifests at the level of a layer or within the whole. The last part examines how Bratton's remark that the book is a design brief, and the fact that the Stack is not used solely by people affects the role of designer.

Networks that self-organize in response to information are one of the most central studies in complex systems theory. A new time series analysis tool for studying self-organizing systems is developed and demonstrated. This method is applied to interacting complex swarms to explore the connection between information transport and group size, providing evidence for Dunbar's numbers having a foundation in network dynamics. A complex network model of information spread is developed. This network infodemic model uses reinforcement learning to simulate connection and opinion adaptation resulting from interaction between units. The model is applied to study polarized populations and echo chamber formation, exploring strategies for network resilience and weakening. The model is straightforward to extend to multilayer networks and networks generated from real world data. By unifying explanation and prediction, the network infodemic model offers a timely step toward understanding global collective behavior.

This work proposes a three-state microscopic opinion formation model based on the stochastic dynamics of the three-state majority-vote model. In order to mimic the heterogeneous compositions of societies, the agent-based model considers two different types of individuals: noise agents and contrarians. We propose an extension of the model for the simulation of the dynamics of financial markets. Agents are represented as nodes in a network of interactions and they can assume any of three distinct possible states (e.g. buy, sell or remain inactive, in a financial context). The time evolution of the state of an agent is dictated by probabilistic dynamics that include both local and global influences. A noise agent is subject to local interactions, tending to assume the majority state of its nearest neighbors with probability 1-q (dissenting from it with a probability given by the noise parameter q). A contrarian is subject to a global interaction with the society as a whole, tending to assume the state of the global minority of said society with probability 1 -q (dissenting from it with probability q). The stochastic dynamics are simulated on complex networks of different topologies, including square lattices, Barabási-Albert networks, Erdös-Rényi random graphs and small-world networks built according to a link rewiring scheme. We perform Monte Carlo simulations to study the second-order phase transition of the system on small-world networks. We perform finite-size scaling analysis and calculate the phase diagram of the system, as well as the standard critical exponents for different values of the rewiring probability. We conclude that the rewiring of the lattice drives the system to different universality classes than that of the three-state majority-vote model on a two dimensional square lattice. The model’s extension for financial markets exhibits the typical qualitative and quantitative features of real financial time series, including heavy-tailed return distributions, volatility clustering and long-term memory for the absolute values of the returns. The histograms of returns are fitted by means of coupled exponential distributions, quantitatively revealing transitions between leptokurtic, mesokurtic and platykurtic regimes in terms of a nonlinear statistical coupling and a shape parameter which describe the complexity of the system.

Ce mémoire part du constat que la visualisation est le parent pauvre de l'approche de modélisation à base d'agents: peu citée, peu mise en avant, elle constitue néanmoins, pour beaucoup de modélisateurs, non seulement leur premier point d'entrée vers la construction de modèles, mais aussi une façon de plus en plus prégnante, de concevoir, vérifier, voire valider des modèles de systèmes complexes. Le domaine de la modélisation à base d'agents, longtemps peu structuré, est en train de progressivement s'organiser en termes de méthodologies de conception, de communication, de description. Le succès du protocole ODD est là pour en témoigner: face à des demandes de représentation de systèmes de plus en plus complexes, les modélisateurs ont besoin de mettre de l'ordre dans leurs façons de modéliser et ils y parviennent. Cependant, il est étonnant de constater qu'aucune place n'est réservée dans ODD, ni dans aucune autre méthodologie approchante, à la façon de visualiser le modèle décrit ou à concevoir. Pour beaucoup de théoriciens de la modélisation, cette étape n'existe tout simplement pas, ou, si elle existe, est considérée comme le lointain produit dérivé d'un modèle déjà conçu, vérifié et validé. Pourtant, l'étude des pratiques de la modélisation à base d'agents révèle tout le contraire: l'aller-retour entre l'écriture et la visualisation d'un modèle fait partie intégrante du quotidien de nombreux chercheurs, comme en témoigne le succès de la plate-forme NetLogo. Cette visualisation, partie d'une démarche intégrée, permet de façon intuitive de vérifier et raffiner aussi bien les comportements individuels des agents que les structures collectives ou émergentes attendues. Poussée à l'extrême, cette pratique se rencontre aussi dans les démarches de modélisation et/ou simulation participative, où la visualisation du modèle sert de médiation entre acteurs et de support aux tâches, collectives, de modélisation. Absente des propositions méthodologiques, la visualisation de modèles à base d'agents se retrouve donc essentiellement délimitée et structurée par des pratiques individuelles, parfois partagées sous la forme de préceptes , mais rarement généralisables au-delà de la conception d'un modèle. Il existe pourtant des façons de visualiser, des manières de chercher à faire ressortir une information spécifique, des méthodes à suivre pour étudier visuellement une abstraction… / Information visualization is the study of interactive visual representations of abstract data to reinforce human cognition. It is very closely associated with data mining issues which allow to explore, understand and analyze phenomena, systems or data masses whose complexity continues to grow today. However, most existing visualization techniques are not suited to the exploration and understanding of datasets that consist of a large number of individual data from heterogeneous sources that share many properties with what are commonly called "complex systems". The reason is often the use of monolithic and centralized approaches. This situation is reminiscent of the modeling of complex systems (social sciences, chemistry, ecology, and many other fields) before progress represented by the generalization of agent-based approaches twenty years ago. In this thesis, I defend the idea that the same approach can be applied with the same success to the field of information visualization. By starting from the now commonly accepted idea that the agent-based models offer appropriate representations the complexity of a real system, I propose to use an approach based on the definition of agent-based visualization models to facilitate visual representation of complex data and to provide innovative support which allows to explore, programmatically and visually, their underlying dynamics. Just like their software counterparts, agent-based visualization models are composed of autonomous graphical entities that can interact and organize themselves, learn from the data they process and as a result adapt their behavior and visual representations. By providing a user the ability to describe visualization tasks in this form, my goal is to allow them to benefit from the flexibility, modularity and adaptability inherent in agent-based approaches. These concepts have been implemented and experimented on the GAMA modeling and simulation platform in which I developed a 3D immersive environment offering the user different point of views and way to interact with agents. Their implementation is validated on models chosen for their properties, supports a linear progression in terms of complexity, allowing us to highlight the concepts of flexibility, modularity and adaptability. Finally, I demonstrate through the particular case of data visualization, how my approach allows, in real time, to represent, to clarify, or even discover their dynamics and how that progress in terms of visualization can contributing,in turn, to improve the modeling of complex systems.

La gestion des changements d’ingénierie, appelée aussi ingénierie du changement, est un domaine de recherche qui s’intéresse à l’étude des changements et des modifications apportés par les concepteurs industriels sur un produit durant l’une des phases de son cycle de vie. Ces changements peuvent exister dans le cadre de renouvellement d’un produit dans un but d’amélioration ou de reconception. Dans la littérature, plusieurs méthodes et outils ont été mis en place pour évaluer l’impact d’un changement en utilisant les dépendances existantes entre les éléments d’un produit, prédire de façon efficace la propagation du changement et évaluer ensuite ses conséquences possibles. Mais aucun d’entre eux n’a tenté de caractériser la relation de dépendance sous la forme d’une fonction polynomiale, en plus des caractérisations classiques par valeurs qualitatives et quantitatives. Nous proposons donc, une nouvelle méthode pour générer les variations possibles d’un changement, afin de modéliser ces variations par paire sous formule analytique, d’étendre les variations par paire aux variations de plusieurs variables et de vérifier formellement la cohérence des résultats obtenus. Visuellement, un graphe de dépendance est construit oú les noeuds représentent les éléments de produit et les arcs portent les fonctions qui les relient. Nos résultats montrent que cette caractérisation fonctionnelle de la dépendance est instructive et permet une propagation de changement et une évaluation efficace. Un modèle géométrique 2D d’un vélo est utilisé pour illustrer l’approche proposée. / Engineering Change Management, also known as Change Engineering, is the research domain that focuses on the study of changes and modifications brought by industrial designers on a product during one of the phases of its life cycle. These changes can exist in the case of product renewal for improvement or re-design. In the literature, several methods and tools have proposed to assess the change impact using the existing dependencies between the product components, predict effectively the change propagation and then evaluate its possible consequences. However, none of them attempted to characterize the dependency relationship in the form of a polynomial function in addition to the qualitative and quantitative values. Therefore, we propose, a new method to generate change variations, in order to model these variations in pairs with an analytical formula, expand the variations in pairs to changes in several variables and formally check the consistency of the results obtained. Visually, a dependency graph is constructed where nodes represent the components of product and edges are the functions that connect them. Our results show that this functional characterization of dependency allows an effective assessment of change propagation. A bike with 2-D geometric model is used to illustrate the proposed approach.

Cette thèse est composée de quatre chapitres.Le premier chapitre est une description préliminaire de la base de données Factset Ownership. Nous en donnons une description statistique et exposons quelques faits stylisés caractérisant notamment la structure du portefeuille des institutions financières et fonds d'investissement, ainsi que la capitalisation boursière des entreprises y étant recensées.Le second chapitre propose une méthode d'évaluation statistique de la similarité entre des paires de portefeuilles d'institutions financières. Une paire statistiquement significative donnant lieu à la création d'un lien de similarité entre ces deux entités, nous sommes en mesure de projeter un réseau à l'origine bi-partite (entre institutions financières et entreprises) en un réseau mono-partite (entre institutions uniquement) afin d'en étudier l'évolution de sa structure au cours du temps. En effet, d'un point de vue économique, il est suspecté que les motifs d'investissements similaires constituent un facteur de risque important de contagion financière pouvant être à l'origine de banqueroutes aux conséquences systémiques significatives.Le troisième chapitre s'intéresse aux comportements collectifs des gestionnaires de fonds d'investissement et, en particulier, à la manière dont la structure du portefeuille de ces fonds prend en compte, en moyenne, de façon optimale les frais de transaction en présence de faibles contraintes d'investissements. Ce phénomène où, dans de nombreuses situations, la médiane ou la moyenne des estimations d'un groupe de personnes est étonnamment proche de la valeur réelle, est connu sous le nom de sagesse de la foule.Le quatrième chapitre est consacré à l'étude simultanée de données de marché. Nous utilisons plus de 6.7 milliards de trades de la base de données Thomson-Reuters Tick History, et de données de portefeuille de la base FactSet Ownership. Nous étudions la dynamique tick-à-tick du carnet d'ordres ainsi que l'action aggrégée, c'est-à-dire sur une échelle de temps bien plus grande, des fonds d'investissement. Nous montrons notamment que la mémoire longue du signe des ordres au marché est bien plus courte en présence de l'action, absolue ou directionnelle, des fonds d'investissement. Réciproquement nous expliquons dans quelle mesure une action caractérisée par une mémoire faible est sujette à du trading directionnel provenant de l'action des fonds d'investissement. / The thesis is divided into four parts.Part I introduces and provides a technical description of the FactSet Ownership dataset together with some preliminary statistics and a set of stylized facts emerging from the portfolio structure of large financial institutions, and from the capitalization of recorded securities.Part II proposes a method to assess the statistical significance of the overlap between pairs of heterogeneously diversified portfolios. This method is then applied to public assets ownership data reported by financial institutions in order to infer statistically robust links between the portfolios of financial institutions based on similar patterns of investment. From an economic point of view, it is suspected that the overlapping holding of financial institution is an important channel for financial contagion with the potential to trigger fire sales and thus severe losses at a systemic level.Part III investigates the collective behaviour of fund manager and, in particular, how the average portfolio structure of institutional investors optimally accounts for transactions costs when investment constraints are weak. The collective ability of a crowd to accurately estimate an unknown quantity is known as the Wisdom of the Crowd. In many situation, the median or average estimate of a group of unrelated individuals is surprisingly close to the true value.In Part IV, we use more than 6.7 billions of trades from the Thomson-Reuters Tick History database and the ownership data from FactSet. We show how the tick-by-tick dynamics of limit order book data depends on the aggregate actions of large funds acting on much larger time scale. In particular, we find that the well-established long memory of marker order signs is markedly weaker when large investment funds trade in a markedly directional way or when their aggregate participation ratio is large. Conversely, we investigate to what respect an asset with a weak memory experiences direction trading from large funds.

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京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第20705号 / 工博第4402号 / 新制||工||1684(附属図書館) / 京都大学大学院工学研究科電気工学専攻 / (主査)教授 引原 隆士, 教授 土居 伸二, 教授 松尾 哲司 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM