One of the questions arising as regards to structured materials is how one can compute their cluster concentrations. Specifically, we are interested in deriving the concentrations of the micro-structures in the NMC (Nickel-Manganese-Cobalt) layer of the cathodes of Li-ion batteries. A simulated annealing approach has been used lately for detecting the structure of the whole lattice which is computationally heavy. Here we propose a mathematical model, called cluster approximation model, in the form of a dynamical system for describing the concentrations of different clusters inside the lattice. However, the dynamical system is hierarchical which requires to be truncated. Truncation of the hierarchical system is performed by the nearest-neighbor closure scheme. Also, a novel framework is proposed for an optimal closure of the dynamical system in order to enhance the accuracy of the model. The parameters of the model are reconstructed by the least square approach as a constrained optimization problem by minimizing the mismatch between the experimental data and the model outputs. The model is validated based on the experimental data on a known Li-ion battery cathode and different approximation schemes are compared. The results clearly show that the proposed approach significantly outperforms the conventional method. / Thesis / Master of Science (MSc)

Les méthodes perturbatives, telle que l’approximation de Born, sont nécessaires pour résoudre les problèmes inhérents à l’ionisation d’atomes et de molécules par impact d’électrons ou de positrons. Afin d’optimiser les calculs nécessaires pour le second terme de l’approximation de Born, nous avons commencé par étudier l’ionisation de l’atome le plus simple : celui d’hydrogène. Nous avons utilisé une base contenant un grand nombre d’états (294) nous permettant d’éviter la relation de fermeture qui nécessite l’introduction d’un paramètre qui représente la valeur moyenne d’excitation. Nos résultats ont montré un bon accord avec l’expérience surtout pour les faibles énergies des électrons éjectés. Nous avons ainsi pu montrer l’importance de la contribution des états du continuum (représentés par des pseudo-états), en particulier pour les transitions de type dipolaire. Pour la double ionisation de l’atome d’hélium, nous avons appliqué la même méthodologie de calcul numérique complet tout en incluant 20 états et pseudo-états intermédiaires et en utilisant une fonction d’onde corrélée d’interaction de configuration, on a trouvé pour les grandes énergies d’incidence (5 keV) que l’effet du terme Born 2 est presque nul. Par contre l’application de « SBA » avec la relation de fermeture pour l’état fondamental et les premiers états excités montre une petite différence avec « FBA » en particulier en dehors de la région du transfert. Dans le cas des faibles énergies d’incidence (601 eV) il était attendu d’obtenir un effet important de « SBA » surtout que des études sur les (e,3-1e) de l’hélium montrent un déplacement du pic principal par rapport à « FBA ». Donc on peut dire que les 20 états intermédiaires contribuent de façon insuffisante et qu’il faudra considérer beaucoup plus d’états / The perturbative methods, such as Born approximation, are necessary to solve the problems concerning the ionization of atoms and molecules by electrons or positrons impacts. In order to use Born approximation in an optimized way, we tested it on the simplest atom « Hydrogen » by using a basis of large amount of intermediate states (294) and complete numerical calculation without using the closure approximation whose application needs the introduction of a parameter which is the excitation mean value. Our results proved a significant agreement with the experiment particularly for small energies of the ejected electrons. We also proved an important contribution of the continuum (represented by the pseudo-states), and particularly the dipolar transition. For the double ionization of Helium atom, we applied the same methodology of complete calculation by including 20 intermediate states and pseudo-states and by using a configuration interaction wave function, we found that for high incident energy (5 keV) the effect of the second term of Born is almost zero. However, the application of the « SBA » with the closure approximation by using the fundamental state and the first excited states show a slight difference relative to the « FBA » particularly outside the transfer region. In case of low incident energy (601 eV), it was expected a crucial effect of the « SBA » especially that previous studies of (e, 3-1e) of Helium show a significant shift of the main peak relative to the « FBA ». So we can say that 20 intermediate states are not enough and the application of the « SBA » needs more states

This thesis addresses issues related to the simulation and optimization of the injection molding of short fiber-reinforced plastics (SFRPs). The injection molding process is modeled by a two phase flow problem. The simulation of the two phase flow is accompanied by the solution of the Folgar-Tucker equation (FTE) for the simulation of the moments of fiber orientation densities. The FTE requires the solution of the so called 'closure problem'', i.e. the representation of the 4th order moments in terms of the 2nd order moments. In the absence of fiber-fiber interactions and isotropic initial fiber density, the FTE admits an analytical solution in terms of elliptic integrals. From these elliptic integrals, the closure problem can be solved by a simple numerical inversion. Part of this work derives approximate inverses and analytical inverses for special cases of fiber orientation densities. Furthermore a method is presented to generate rational functions for the computation of arbitrary moments in terms of the 2nd order closure parameters. Another part of this work treats the determination of effective material properties for SFRPs by the use of FFT-based homogenization methods. For these methods a novel discretization scheme, the 'staggered grid'' method, was developed and successfully tested. Furthermore the so called 'composite voxel'' approach was extended to nonlinear elasticity, which improves the approximation of material properties at the interfaces and allows the reduction of the model order by several magnitudes compared to classical approaches. Related the homogenization we investigate optimal experimental designs to robustly determine effective elastic properties of SFRPs with the least number of computer simulations. Finally we deal with the topology optimization of injection molded parts, by extending classical SIMP-based topology optimization with an approximate model for the fiber orientations. Along with the compliance minimization by topology optimization we also present a simple shape optimization method for compensation of part warpage for an black-box production process.:Acknowledgments v Abstract vii Chapter 1. Introduction 1 1.1 Motivation 1 1.2 Nomenclature 3 Chapter 2. Numerical simulation of SFRP injection molding 5 2.1 Introduction 5 2.2 Injection molding technology 5 2.3 Process simulation 6 2.4 Governing equations 8 2.5 Numerical implementation 18 2.6 Numerical examples 25 2.7 Conclusions and outlook 27 Chapter 3. Numerical and analytical methods for the exact closure of the Folgar-Tucker equation 35 3.1 Introduction 35 3.2 The ACG as solution of Jeffery's equation 35 3.3 The exact closure 36 3.4 Carlson-type elliptic integrals 37 3.5 Inversion of R_D-system 40 3.6 Moment tensors of the angular central Gaussian distribution on the n-sphere 49 3.7 Experimental evidence for ACG distribution hypothesis 54 3.8 Conclusions and outlook 60 Chapter 4. Homogenization of SFRP materials 63 4.1 Introduction 63 4.2 Microscopic and macroscopic model of SFRP materials 63 4.3 Effective linear elastic properties 65 4.4 The staggered grid method 68 4.5 Model order reduction by composite voxels 80 4.6 Optimal experimental design for parameter identification 93 Chapter 5. Optimization of parts produced by SFRP injection molding 103 5.1 Topology optimization 103 5.2 Warpage compensation 110 Chapter 6. Conclusions and perspectives 115 Appendix A. Appendix 117 A.1 Evaluation of R_D in Python 117 A.2 Approximate inverse for R_D in Python 117 A.3 Inversion of R_D using Newton's/Halley's method in Python 117 A.4 Inversion of R_D using fixed point method in Python 119 A.5 Moment computation using SymPy 120 A.6 Fiber collision test 122 A.7 OED calculation of the weighting matrix 123 A.8 OED Jacobian of objective and constraints 123 Appendix B. Theses 125 Bibliography 127 / Diese Arbeit befasst sich mit Fragen der Simulation und Optimierung des Spritzgießens von kurzfaserverstärkten Kunststoffen (SFRPs). Der Spritzgussprozess wird durch ein Zweiphasen-Fließproblem modelliert. Die Simulation des Zweiphasenflusses wird von der Lösung der Folgar-Tucker-Gleichung (FTE) zur Simulation der Momente der Faserorientierungsdichten begleitet. Die FTE erfordert die Lösung des sogenannten 'Abschlussproblems'', d. h. die Darstellung der Momente 4. Ordnung in Form der Momente 2. Ordnung. In Abwesenheit von Faser-Faser-Wechselwirkungen und anfänglich isotroper Faserdichte lässt die FTE eine analytische Lösung durch elliptische Integrale zu. Aus diesen elliptischen Integralen kann das Abschlussproblem durch eine einfache numerische Inversion gelöst werden. Ein Teil dieser Arbeit leitet approximative Inverse und analytische Inverse für spezielle Fälle von Faserorientierungsdichten her. Weiterhin wird eine Methode vorgestellt, um rationale Funktionen für die Berechnung beliebiger Momente in Bezug auf die Abschlussparameter 2. Ordnung zu generieren. Ein weiterer Teil dieser Arbeit befasst sich mit der Bestimmung effektiver Materialeigenschaften für SFRPs durch FFT-basierte Homogenisierungsmethoden. Für diese Methoden wurde ein neuartiges Diskretisierungsschema 'staggerd grid'' entwickelt und erfolgreich getestet. Darüber hinaus wurde der sogenannte 'composite voxel''-Ansatz auf die nichtlineare Elastizität ausgedehnt, was die Approximation der Materialeigenschaften an den Grenzflächen verbessert und die Reduzierung der Modellordnung um mehrere Größenordnungen im Vergleich zu klassischen Ansätzen ermöglicht. Im Zusammenhang mit der Homogenisierung untersuchen wir optimale experimentelle Designs, um die effektiven elastischen Eigenschaften von SFRPs mit der geringsten Anzahl von Computersimulationen zuverlässig zu bestimmen. Schließlich beschäftigen wir uns mit der Topologieoptimierung von Spritzgussteilen, indem wir die klassische SIMP-basierte Topologieoptimierung um ein Näherungsmodell für die Faserorientierungen erweitern. Neben der Compliance-Minimierung durch Topologieoptimierung stellen wir eine einfache Formoptimierungsmethode zur Kompensation von Teileverzug für einen Black-Box-Produktionsprozess vor.:Acknowledgments v Abstract vii Chapter 1. Introduction 1 1.1 Motivation 1 1.2 Nomenclature 3 Chapter 2. Numerical simulation of SFRP injection molding 5 2.1 Introduction 5 2.2 Injection molding technology 5 2.3 Process simulation 6 2.4 Governing equations 8 2.5 Numerical implementation 18 2.6 Numerical examples 25 2.7 Conclusions and outlook 27 Chapter 3. Numerical and analytical methods for the exact closure of the Folgar-Tucker equation 35 3.1 Introduction 35 3.2 The ACG as solution of Jeffery's equation 35 3.3 The exact closure 36 3.4 Carlson-type elliptic integrals 37 3.5 Inversion of R_D-system 40 3.6 Moment tensors of the angular central Gaussian distribution on the n-sphere 49 3.7 Experimental evidence for ACG distribution hypothesis 54 3.8 Conclusions and outlook 60 Chapter 4. Homogenization of SFRP materials 63 4.1 Introduction 63 4.2 Microscopic and macroscopic model of SFRP materials 63 4.3 Effective linear elastic properties 65 4.4 The staggered grid method 68 4.5 Model order reduction by composite voxels 80 4.6 Optimal experimental design for parameter identification 93 Chapter 5. Optimization of parts produced by SFRP injection molding 103 5.1 Topology optimization 103 5.2 Warpage compensation 110 Chapter 6. Conclusions and perspectives 115 Appendix A. Appendix 117 A.1 Evaluation of R_D in Python 117 A.2 Approximate inverse for R_D in Python 117 A.3 Inversion of R_D using Newton's/Halley's method in Python 117 A.4 Inversion of R_D using fixed point method in Python 119 A.5 Moment computation using SymPy 120 A.6 Fiber collision test 122 A.7 OED calculation of the weighting matrix 123 A.8 OED Jacobian of objective and constraints 123 Appendix B. Theses 125 Bibliography 127