This thesis work comprises the working and simulation procedures being involved in simulating motion capture data in AnyBody Modeling System. The motion capture data used in this thesis are ballet movements from dancers of Östgöta ballet and dance academy. The ballet movements taken into consideration are the arabesque on demi-pointe and pirouette. The arabesque on demi-pointe was performed by two dancers but the pirouette is performed by only one dancer. The method involved recording ballet movements by placing markers on the dancer's body and using this motion capture data as input to AnyBody Modeling System to create a musculoskeletal simulation. The musculoskeletal modeling involved creating a very own Qualisys marker protocol for the markers placed on the ballet dancers. Then implementing the marker protocol onto a human model in AnyBody Modeling System by making use of the AnyBody Managed Modeling Repository (TM) and obtain the kinematics from the motion capture. To best fit the human model to the dancer's anthropometry, scaling of the human model is done, environmental conditions such as the force plates are provided. An optimization algorithm is conducted for the marker positions to best fit the dancer's anthropometry by running parameter identification. From the kinematics of the motion capture data, we simulate the inverse dynamics in AnyBody Modeling System. The simulations explain a lot of parameters that describe the ballet dancers. Results such as the center of mass, the center of pressure, muscle activation, topple angle are presented and discussed. Moreover, we compare the models of the dancers and draw conclusions about body balance, effort level, and muscles activated during the ballet movements.

Cette thèse traite de l'identification des paramètres du point de vue de l'optimisation et du contrôle de suivi distribué des systèmes multi-agents d'ordre fractionnaire (FOMASs) en tenant compte des retards, des perturbations externes, de la non-linéarité inhérente, des incertitudes des paramètres et de l'hétérogénéité dans le cadre d'une topologie de communication fixe non dirigée / dirigée. Plusieurs contrôleurs efficaces sont conçus pour réaliser avec succès le contrôle de suivi distribué des FOMASs dans différentes conditions. Plusieurs types d'algorithmes d'optimisation de l'intelligence artificielle et leurs versions modifiées sont appliquées pour identifier les paramètres inconnus des FOMASs avec une grande précision, une convergence rapide et une grande robustesse. Il est à noter que cette thèse fournit un lien prometteur entre la technique d'intelligence artificielle et le contrôle distribué. / This thesis deals with the parameter identification from the viewpoint of optimization and distributed tracking control of fractional-order multi-agent systems (FOMASs) considering time delays, external disturbances, inherent nonlinearity, parameters uncertainties, and heterogeneity under fixed undirected/directed communication topology. Several efficient controllers are designed to achieve the distributed tracking control of FOMASs successfully under different conditions. Several kinds of artificial intelligence optimization algorithms andtheir modified versions are applied to identify the unknown parameters of the FOMASs with high accuracy, fast convergence and strong robustness. It should be noted that this thesis provides a promising link between the artificial intelligence technique and distributed control.

Electromagnetic welding is an innovative, high-speed technology to manufacture mixed material joints. In this dissertation, an experimental-numerical method is presented to identify robust process windows of aluminum-copper and aluminum-steel compounds. The microstructural characteristics of these joints were investigated in detail. Moreover, an evaluation of the joint quality is presented and different numerical models were introduced for the simulation of macroscopic and microscopic effects. To improve the accuracy of the simulations, the strain rate sensitivity of the materials must be considered. For this purpose a high-speed setup for the identification of relevant viscoplastic material parameters, comprising an inverse evaluation strategy, was developed.

In der Photovoltaikindustrie wird der Diamantdrahtsägeprozess für die Fertigung kristalliner Siliziumwafer eingesetzt. In dieser Arbeit wird ein dynamisches Modell des Drahtsägeprozesses entwickelt, das die Simulation relevanter Prozessvariablen über die Prozesszeit und über die Ausdehnung des Drahtfeldes zulässt. Den Kern der Modellierung bildet ein parametrisches Abtragmodell, das die Abtragrate in Funktion verschiedener Prozessvariablen beschreibt. Die Parameter dieses Modells werden anhand von Messdaten identifiziert. Basierend auf dem validierten Modell werden Ansätze zur Rezeptoptimierung untersucht mit dem Ziel, die Produktivität zu steigern. Abschliessend wird ein ausgewählter Ansatz aus der Rezeptoptimierung experimentell validiert. Aus der Versuchsreihe geht hervor, dass mit den entwickelten Ansätzen eine wesentliche Reduktion der Prozesszeit möglich ist.:1. Einleitung 1.1. Einordnung der Arbeit 1.2. Beschreibung des Drahtsägeprozesses mit Diamantdraht 1.3. Technisch-wissenschaftliche Zielsetzungen 1.4. Stand der Technik 1.5. Gliederung der Arbeit 2. Modellierung des Drahtsägeprozesses 2.1. Überblick und Notation 2.2. Modell für den Kontakt zwischen Draht und Siliziumbrick 2.3. Parametrisches Abtragmodell 2.4. Drahttransformationsmodelle 2.5. Rezeptmodell 2.6. Überblick über das Gesamtmodell 2.7. Implementierung in der Simulationsumgebung 3. Identifikation der Modellparameter und Modellvalidierung 3.1. Messdaten und Experimente 3.2. Methodik der Parameteridentifikation 3.3. Ergebnisse und Diskussion 4. Ansätze zur Rezeptoptimierung 4.1. Zielsetzungen und Grundlagen 4.2. Analyse der Prozessvariablen im quasistationären Zustand 4.3. Beschreibung verschiedener Methoden zur Erhöhung des Abtrages 4.4. Simulationsbasierter Vergleich verschiedener Rezepte 5. Experimentelle Validierung der Rezeptoptimierung 5.1. Überlegungen zur Planung und Durchführung der Versuche 5.2. Abgleich mit dem Simulationsmodell 5.3. Auswertung und Diskussion der Versuchsergebnisse 6. Zusammenfassung und Ausblick / In the photovoltaic industry, the diamond wire sawing process is used for the production of crystalline silicon wafers. In this thesis, a dynamic model of the wire sawing process is presented, which enables the simulation of relevant process variables over the process time and the extension of the wire web. The model comprises a parametric material removal model, which describes the removal rate as a function of different process variables. The parameters of this model are identified using experimental data. Based on the validated model, different approaches to the optimization of the recipe are analyzed with the aim of increasing the productivity of the process. Finally, a selected approach is experimentally validated. The series of experiments reveals that a substantial reduction of the process time is achievable using the developed approaches.:1. Einleitung 1.1. Einordnung der Arbeit 1.2. Beschreibung des Drahtsägeprozesses mit Diamantdraht 1.3. Technisch-wissenschaftliche Zielsetzungen 1.4. Stand der Technik 1.5. Gliederung der Arbeit 2. Modellierung des Drahtsägeprozesses 2.1. Überblick und Notation 2.2. Modell für den Kontakt zwischen Draht und Siliziumbrick 2.3. Parametrisches Abtragmodell 2.4. Drahttransformationsmodelle 2.5. Rezeptmodell 2.6. Überblick über das Gesamtmodell 2.7. Implementierung in der Simulationsumgebung 3. Identifikation der Modellparameter und Modellvalidierung 3.1. Messdaten und Experimente 3.2. Methodik der Parameteridentifikation 3.3. Ergebnisse und Diskussion 4. Ansätze zur Rezeptoptimierung 4.1. Zielsetzungen und Grundlagen 4.2. Analyse der Prozessvariablen im quasistationären Zustand 4.3. Beschreibung verschiedener Methoden zur Erhöhung des Abtrages 4.4. Simulationsbasierter Vergleich verschiedener Rezepte 5. Experimentelle Validierung der Rezeptoptimierung 5.1. Überlegungen zur Planung und Durchführung der Versuche 5.2. Abgleich mit dem Simulationsmodell 5.3. Auswertung und Diskussion der Versuchsergebnisse 6. Zusammenfassung und Ausblick

[ES] El acceso a una atención sanitaria de alta calidad es un marcador importante del desarrollo de las sociedades humanas. Los aportes tecnológicos a la medicina han mostrado un potencial relevante para descubrir procedimientos efectivos a nivel preventivo, diagnóstico y terapéutico. En particular, los métodos computacionales permiten el procesamiento eficaz de datos médicos y, por tanto, pueden modelar sistemas biológicos complejos. Esto ha influido en el desarrollo de la Medicina Personalizada (MP) durante las últimas décadas, donde la obtención de conocimiento específico de cada caso permite realizar intervenciones a medida, todo ello a un coste de recursos accesible. La simulación de remodelación ósea es un campo prometedor en el contexto de la MP. Predecir un proceso de adaptación ósea en un caso concreto puede dar lugar a numerosas aplicaciones en el campo de las enfermedades óseas, tanto a nivel clínico como experimental. Mediante la combinación del Método de Elementos Finitos (FEM) y los algoritmos de remodelación ósea, es posible obtener modelos numéricos de un hueso específico a partir de datos médicos (por ejemplo, una tomografía computarizada). Todo ello puede dar lugar a una revolución en la medicina personalizada. / [CA] L'accés a una atenció sanitària d'alta qualitat és un marcador important del desenvolupament de les societats humanes. Les aportacions tecnològiques a la medicina han mostrat un potencial rellevant per a descobrir procediments efectius a nivell preventiu, diagnòstic i terapèutic. En particular, els mètodes computacionals permeten el processament eficaç de dades mèdiques i, per tant, poden modelar sistemes biològics complexos. Això ha influït en el desenvolupament de la Medicina Personalitzada (MP) durant les últimes dècades, on l'obtenció de coneixement específic de cada cas permet realitzar intervencions a mesura, tot això a un cost de recursos accessible. La simulació de remodelació òssia és un camp prometedor en el context de la MP. Predir un procés d'adaptació òssia en un cas concret pot donar lloc a nombroses aplicacions en el camp de les malalties òssies, tant a nivell clínic com experimental. Mitjançant la combinació del Mètode d'Elements Finits (*FEM) i els algorismes de remodelació òssia, és possible obtindre models numèrics d'un os específic a partir de dades mèdiques (per exemple, una tomografia computada). Tot això pot donar lloc a una revolució en la medicina personalitzada. / [EN] Access to high-quality healthcare is an important marker of the development of human societies. Technological contributions to medicine have shown relevant potential to discover effective procedures at a preventive, diagnostic and therapeutic level. In particular, computational methods enable efficient processing of medical data and can therefore model complex biological systems. This has influenced the development of Personalized Medicine (PM) over recent decades, where obtaining specific knowledge of each case allows for tailored interventions, all at an affordable resource cost. Simulation of bone remodeling is a promising field in the context of PM. Predicting a bone adaptation process in a specific case can lead to numerous applications in the field of bone diseases, both clinically and experimentally. By combining the Finite Element Method (FEM) and bone remodeling algorithms, it is possible to obtain numerical models of a specific bone from medical data (for example, a CT scan). All of this can lead to a revolution in personalized medicine. / Thanks to the Valencian funding programme FDGENT/2018, for providing economic resources to develop this long-term work. / Gutiérrez Gil, J. (2023). Personalization of Bone Remodelling Simulation Models for Clinical Applications [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/202059

This thesis deals with regularization parameter selection methods in the context of Tikhonov-type regularization with Poisson distributed data, in particular the reconstruction of images, as well as with the identification of the volatility surface from observed option prices. In Part I we examine the choice of the regularization parameter when reconstructing an image, which is disturbed by Poisson noise, with Tikhonov-type regularization. This type of regularization is a generalization of the classical Tikhonov regularization in the Banach space setting and often called variational regularization. After a general consideration of Tikhonov-type regularization for data corrupted by Poisson noise, we examine the methods for choosing the regularization parameter numerically on the basis of two test images and real PET data. In Part II we consider the estimation of the volatility function from observed call option prices with the explicit formula which has been derived by Dupire using the Black-Scholes partial differential equation. The option prices are only available as discrete noisy observations so that the main difficulty is the ill-posedness of the numerical differentiation. Finite difference schemes, as regularization by discretization of the inverse and ill-posed problem, do not overcome these difficulties when they are used to evaluate the partial derivatives. Therefore we construct an alternative algorithm based on the weak formulation of the dual Black-Scholes partial differential equation and evaluate the performance of the finite difference schemes and the new algorithm for synthetic and real option prices.

This thesis deals with regularization parameter selection methods in the context of Tikhonov-type regularization with Poisson distributed data, in particular the reconstruction of images, as well as with the identification of the volatility surface from observed option prices. In Part I we examine the choice of the regularization parameter when reconstructing an image, which is disturbed by Poisson noise, with Tikhonov-type regularization. This type of regularization is a generalization of the classical Tikhonov regularization in the Banach space setting and often called variational regularization. After a general consideration of Tikhonov-type regularization for data corrupted by Poisson noise, we examine the methods for choosing the regularization parameter numerically on the basis of two test images and real PET data. In Part II we consider the estimation of the volatility function from observed call option prices with the explicit formula which has been derived by Dupire using the Black-Scholes partial differential equation. The option prices are only available as discrete noisy observations so that the main difficulty is the ill-posedness of the numerical differentiation. Finite difference schemes, as regularization by discretization of the inverse and ill-posed problem, do not overcome these difficulties when they are used to evaluate the partial derivatives. Therefore we construct an alternative algorithm based on the weak formulation of the dual Black-Scholes partial differential equation and evaluate the performance of the finite difference schemes and the new algorithm for synthetic and real option prices.