L’objectif du travail de thèse a été la mise en place de deux modélisations multi-physiques fondées sur des fondements théoriques communs mais appliquées à deux domaines de la recherche scientifique très différents: i) l’étude du comportement du béton au jeune âge pour la prévention de la fissuration précoce- ii) l’analyse des phénomènes physiques, chimiques et biologiques qui gouvernent la croissance et l’évolution de la tumeur cancéreuse. Le développement d’un outil numérique pour la modélisation du béton au jeune âge est très important pour la conception de structures durables. Le modèle développé pendant la thèse doctorale a été implanté sur le code aux éléments finis Cast3M, puis validé expérimentalement. Il permet de multiples applications: étude des sollicitations et des phénomènes de fissuration au jeune âge, gradients thermiques et hydriques, prédiction du retrait endogène et de dessiccation, étude de l’inhibition de l’hydratation causée par le séchage, prédiction du fluage et de la redistribution des contraintes associées, étude des réparations. Les équations qui gouvernent le comportement thermo-hydro-chemo-mécanique du béton au jeune âge ont plusieurs analogies formelles avec celles qui sont typiquement à la base de la modélisation de la croissance des tumeurs cancéreuses. L'élargissement de l'analyse numérique dans le domaine médical est d’un grand intérêt social en complément de l’intérêt scientifique. Les équations utilisées pour le béton ont été réadaptées, et le modèle mathématique obtenu a été implanté dans Cast3M. Les premiers résultats du modèle ont été satisfaisants et qualitativement très proches des données expérimentales de la littérature dans ce domaine. / The aim of the PhD thesis has been the development of two multi-physics models based on common theoretical basis, but applied to two very different areas: i) the study of the behavior of concrete at early age, essentially for the prevention of early cracking and related issues- ii) the analysis of physical, chemical and biological processes that govern growth and development of cancer. The development of a numerical tool to model concrete at early age is of great importance for the design of durable and sustainable structures. The model has been implemented on the finite element code CAST3M (developed by CEA), also it was validated and nowadays allows multiple applications: study of stresses and cracking phenomena in young concrete, thermal and hygral gradients, autogenous and drying shrinkage, inhibition of hydration caused by drying, creep, stress redistribution, study repairs, etc.. In the fight against cancer, it is clear that the advance of medical strategies based on numerical analysis have a critical scientific interest and can have a great social impact. The equations which govern the thermo-hydro-chemo-mechanical behavior of concrete at early age have may formal analogies with those used to model tumor growth. Hence, these equations have been readapted and a novel mathematical model for tumor growth has been developed. The model was implemented in Cast3M and the first numerical results have been encouraging since very close to the experimental data present in the literature.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第23502号 / 工博第4914号 / 新制||工||1768(附属図書館) / 京都大学大学院工学研究科機械理工学専攻 / (主査)教授 平方 寛之, 教授 北條 正樹, 教授 嶋田 隆広, 教授 井上 康博 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Visualizing and interacting with engineering analysis results can provide valuable insights into a system's performance and aid in engineering decision-making. Currently, the majority of analysis codes are developed as isolated solutions focusing only on the most prominent physical influence to a system, such as thermal, structural, fluid, etc. Frequently, more than one of these physical influences combined to force engineers to evaluate complex, coupled systems. Coupled analysis codes are becoming more common place tools for engineers demanding high fidelity simulations of complex systems. External code coupling solutions are emerging to permit generic coupling of separate, world class CAE solvers thus providing a more general class of multidisciplinary simulations. The true value of an engineering analysis is determined by the accuracy of the analysis code and the ability to interpret all of the significant information contained in the analysis results. Post-processing visualization tools have long been valued for their ability to aid engineers in interpreting all of the significant information contained in non-coupled CAE analysis results. The tie between non-coupled CAE solvers and post-processing visualization tools is poorly defined and currently few general post-processing visualization tools exist capable of interpreting a wide range of differing CAE results. The few tools capable of general post-processing require extensive development of dozens of data readers or translators to accommodate the slew of varying CAE data formats. As coupled CAE solutions emerge, a need exists to standardize the data exchange between CAE solvers and post-processing visualization tools. A format for this standard CAE data exchange, similar to IGES for CAD/CAM data, is proposed. The object of this research is to bridge the gap between external code couplers and post-processing visualization tools to initiate visualization and interaction with these externally coupled results. This fusion of two dissimilar technologies affords a greater level of result interpretation to support engineering decision-making. A general integration architecture is presented and a proof of concept with industry leading tools is developed to demonstrate the benefits of a tight integration between external code couplers and post-processing visualization tools. Examples are presented of visualizing externally coupled results. This research lets the engineer significantly interact with and visualize more complex problems, solved in preferred world class tools, in a timely and streamlined manner.

The incorporation of detailed chemistry models in internal combustion engine simulations is becoming mandatory as new combustion strategies and lower global emissions limits are setting the path towards a more efficient engine cycle simulation tool. In this report, the computational capability of the stochastic-based Kinetics SRM engine suite by CMCL Innovations is evaluated in depth. With the main objectives of this research to create a multi-physics co-simulation framework and improve the traditional engine modelling approach of individual simulation of engine system parts, the Kinetics SRM code was coupled with a GT-SUITE engine model to fill in the gap of accurate emissions predictions from one-dimensional simulation tools. The system was validated against testing points collected from the AJ133 V8 5L GDI engine running on the NEDC. The Kinetics SRM model is further advanced through a sensitivity analysis for the “unknown” internal parameters of the chemistry tool. A set of new parameters’ values has been established that gives the best overall trade-off between prediction accuracy and computational time. However, it still showed high percentage errors in modelling the emissions and it was discovered that the specific software package currently cannot simulate directed injection events. This is the first time a Kinetics SRM/GT-SUITE coupled code is employed to model a full 8-cylinder GDI SI engine. The approach showed some limitations regarding the Kinetics SRM and that in many cases is limited to trend analysis. The coupled engine – combustion emissions model is then linked with an exhaust aftertreatment system model in MATLAB Simulink, creating a multi-physics model-based co-simulation framework of engine performance, combustion characterisation, in-cylinder emissions formation and aftertreatment efficiency.

Scanning Laser Epitaxy (SLE) is a new laser-based layer-by-layer generative manufacturing technology being developed in the Direct Digital Manufacturing Laboratory at Georgia Tech. SLE allows creation of geometrically complex three-dimensional components with as-desired microstructure through controlled melting and solidification of stationary metal-alloy powder placed on top of like-chemistry substrates. The proposed research seeks to garner knowledge about the fundamental physics of SLE through simulation-based studies and apply this knowledge for hot section turbine component repair and ultimately extend the process capability to enable one-step manufacture of complex gas turbine components. Prior methods of repair specifically for hot-section Ni-base superalloys have shown limited success, failed to consistently maintain epitaxy in the repaired part and suffered from several mechanical and metallurgical defects. The use of a fine focused laser beam, close thermal control and overlapping raster scan pattern allows SLE to perform significantly better on a range of so-called “non-weldable” Ni-base superalloys. The process capability is expanded further through closed-loop feedback control of melt pool temperature using an infra-red thermal camera. The process produces dense, crack-free and epitaxial deposit for single-crystal (SX) (CMSX4), equiaxed (René-80, IN 100) and directionally solidified (DS) (René-142) Ni-based superalloys. However, to enable consistent and repeatable production of defect-free parts and future commercial implementation of the technology several concerns related to process capabilities and fundamental physics need to be addressed. To explore the process capability, the fabricated components are characterized in terms of several geometrical, mechanical and metallurgical parameters. An active-contour based image analysis technique has been developed to obtain several microstructural responses from the optical metallography of sample cross-sections and the process goes through continuous improvement through optimization of the process parameters through subsequent design of experiments. The simulation-based study is aimed at developing a multiphysics model that captures the fundamental physics of the fabrication process and allows the generation of constitutive equations for microstructural transitions and properties. For this purpose, a computational fluid dynamics (CFD) finite-volume solver is used to model the melting and solidification process. The development work also focuses on studying process response to different superalloy materials and implementing a multivariate statistical process control that allows efficient management and optimization of the design parameter space. In contrast to the prior work on single-bead laser scan, the model incorporates the raster scan pattern in SLE and the temperature dependent local property variations. The model is validated through thermal imaging data. The flow-thermal model is further tied to an empirical microstructural model through the active-contour based optical image analysis technique, which enables the identification of several microstructural transitions for laser beam describing a raster scan pattern. The CFD model can effectively be coupled with finite element solver to assess the stress and deformation and can be coupled with meso-scale models (Cellular Automata) to predict different microstructural evolutions. The research thus allows extending the SLE process to different superalloy materials, performs statistical monitoring of the process, and studies the fundamental physics of the process to enable formulation of constitutive relations for use in closed-loop feedback control; thus imparting ground breaking capability to SLE to fabricate superalloy components with as-desired microstructures.

<div>Electronics have now become a part of our daily life and therefore the reliability of microelectronics cannot be overlooked. As the Moore's law era comes to an end, various new system-level innovations (e.g., 3D packaging, evolution of packaging material to molding compounds) with constant scaling of transistors have resulted in increasingly complicated integrated circuits (ICs) configurations. The reliability modeling of complex ICs is a nontrivial concern for a variety of reasons. For example, ever since 2004, self-heating effect (SHE) has become an important reliability concern for ICs. Currently, many groups have developed thermal predictive models for transistors, circuits, and systems. In order to describe SHE self-consistently, the modeling framework must account for correlated self-heating within the ICs. This multi-scales nature of the self-consistency problem is one of the difficult factors poses an important challenge to self-consistent modeling. In addition, coupling between different physical effects within IC further complicates the problem.</div><div><br></div><div>In this thesis, we discuss three challenges, and their solutions related to an IC's reliability issues. We (i) generalize the classical effective medium theory (EMT) to account for anisotropic, heterogeneous system; (ii) develop computationally efficient a physics-based thermal compact model for a packaged ICs to predict junction temperature in the transistor based on the EMT model, and image charge theory. Our thermal compact model bridges different length scales among the sources and rest of the system. Finally (iii) propose the modeling framework of electrical chip package interaction (CPI) due to charge transport within mold compounds by coupling moisture diffusion, electric distribution, and ions transport. The proposed modeling framework not only addresses the three major modeling challenges discussed earlier, but also provides deep and fundamental insights regarding the performance and reliability of modern ICs. </div>

La prévision des incendies de forêt reste un défi puisque vitesse et direction de propagation dépendent des interactions multi-échelles entre la végétation, la topographie du terrain et les conditions météorologiques. Un modèle à l’échelle régionale peut donc difficilement prendre en compte le détail des processus physiques mis en jeu. Toute modélisation est entachée de nombreuses incertitudes (modélisation incomplète, méconnaissance du terrain, de la végétation et des interactions flamme/atmosphère, etc.) qu’il est nécessaire de quantifier et de corriger. Ces travaux de thèse proposent ainsi une modélisation régionale des incendies qui a des meilleures capacités de simulation et prévision, basée sur une évaluation des modèles et l’assimilation de données. L’évaluation de modèles a consisté à développer des simulations multi-physiques à l’échelle de la flamme, incluant la résolution des équations de Navier-Stokes réactives, l’évaluation du transfert radiatif vers la végétation, la construction d’un modèle de pyrolyse de la végétation ainsi que la modélisation de l’interface flamme/végétation afin de mieux comprendre la dynamique des incendies. La seconde approche proposée a consisté à mettre en place un prototype d’assimilation de données pour le suivi de la propagation du front de feu. L’idée est de rectifier la trajectoire simulée du front au fur et à mesure que de nouvelles observations sont mises à disposition, la différence entre les positions observées et simulées du front étant traduite en une correction des paramètres de vitesse de propagation ou directement de la position du front via l’algorithme du filtre de Kalman d’ensemble. Ces approches, tenant compte des incertitudes à la fois sur la modélisation des incendies et sur les observations disponibles, permettent ainsi d’améliorer la prévision de la dynamique des feux ainsi que des émissions atmosphériques, ce qui constitue un enjeu de taille pour la protection civile et environnementale. / Because wildfires feature complex multi-physics occurring at multiple scales, our ability to accurately simulate their behavior at large regional scales remains limited. The mathematical models proposed to simulate wildfire spread are currently limited because of their inability to cover the entire range of relevant scales, because also of knowledge gaps and/or inaccuracies in the description of the physics as well as inaccuracies in the description of the controlling input parameters (i.e., the vegetation, topographical and meteorological properties). For this purpose, the uncertainty in regional-scale wildfire spread modeling must be quantified and reduced. In this context, the goals of this thesis are two-fold. First, multi-physics detailed simulations of fire propagation, solving for the flame structure using Navier-Stokes equations for multi-species reacting flow and including radiation heat transfer, biomass pyrolysis as well as a flame/vegetation interface, were performed at the flame scale. These simulations were compared to measurements to provide a comprehensive understanding of the mechanisms underlying fire propagation. Second, the use of a data-driven simulator that sequentially integrates remote sensing measurements and relies on an empirical spread model was explored for regional-scale fire front tracking. The idea underlying this data assimilation strategy was to translate the differences in the observed and simulated fire front locations into a correction of the input parameters of the empirical model or directly of the fire front location via the ensemble Kalman filter algorithm. Since these two approaches account for uncertainties in fire spread modeling and measurements, they improve our ability to forecast wildfire dynamics and plume emissions. These challenges have been identified as a valuable research objective with direct applications in fire emergency response for civil defense and environmental protection.

The quality of parts fabricated using Laser Solid Freeform Fabrication (LSFF) is highly dependent on the physical phenomena and operating parameters which govern the process. For instance, the thermal stress patterns and intensity, induced throughout the process domain due to the layer-by-layer material deposition and the temperature distribution characteristics, contribute significantly to potential delamination and crack formation across the fabricated part. In this research, some of the main features as well as drawbacks of this technique are studied through a multi-physics analysis of the process. For this purpose, a coupled time-dependent 3D model is developed with which the geometry of the deposited material as well as temperature and thermal stress fields across the process domain can be predicted. In the proposed approach, coupled thermal and stress domains are numerically obtained assuming a decoupled interaction between the laser beam and powder stream. To predict the geometry of the deposited material, once the melt pool boundary is obtained, the process domain is discretized in a cross-sectional fashion based on the powder feed rate, elapsed time, and intersection of the melt pool and powder stream projected on the substrate. Layers of additive material are then added onto the non-planar domain. The main process parameters affected by a multilayer deposition due to the formation of non-planar surfaces, such as powder catchment, are incorporated into the modelling approach to enhance the accuracy of the results. To demonstrate the proposed algorithm and to study the main features of the process, a four-layer thin wall of AISI 304L steel on a substrate of the same material is numerically and experimentally fabricated. The numerical analyses along with the experimental results are then used to investigate the correlation between the temperature-thermal stress fields and crack formation across the fabricated parts. The trend of the results reveals that by preheating the substrate prior to the fabrication process, it is possible to substantially reduce the formed micro-cracks. To demonstrate the feasibility of preheating on the reduction of micro-cracks, several simulations and experiments are performed in which a crack-free result is obtained, with a 22 per cent reduction in thermal stresses when the substrate is preheated to 800 K. The numerical and experimental results are also used to study the circumstances of the microstructural formation during the fabrication process. To conclude this research, the developed modelling approach is further extended to briefly discuss the effects of the path patterns and the main operating parameters on the outcomes of the process. The effects of the material properties and their variations on the temperature distributions and thermal stress fields are studied by fabrication of a thin wall of two Stellite 6 layers and two Ti layers on a stainless steel substrate.

The quality of parts fabricated using Laser Solid Freeform Fabrication (LSFF) is highly dependent on the physical phenomena and operating parameters which govern the process. For instance, the thermal stress patterns and intensity, induced throughout the process domain due to the layer-by-layer material deposition and the temperature distribution characteristics, contribute significantly to potential delamination and crack formation across the fabricated part. In this research, some of the main features as well as drawbacks of this technique are studied through a multi-physics analysis of the process. For this purpose, a coupled time-dependent 3D model is developed with which the geometry of the deposited material as well as temperature and thermal stress fields across the process domain can be predicted. In the proposed approach, coupled thermal and stress domains are numerically obtained assuming a decoupled interaction between the laser beam and powder stream. To predict the geometry of the deposited material, once the melt pool boundary is obtained, the process domain is discretized in a cross-sectional fashion based on the powder feed rate, elapsed time, and intersection of the melt pool and powder stream projected on the substrate. Layers of additive material are then added onto the non-planar domain. The main process parameters affected by a multilayer deposition due to the formation of non-planar surfaces, such as powder catchment, are incorporated into the modelling approach to enhance the accuracy of the results. To demonstrate the proposed algorithm and to study the main features of the process, a four-layer thin wall of AISI 304L steel on a substrate of the same material is numerically and experimentally fabricated. The numerical analyses along with the experimental results are then used to investigate the correlation between the temperature-thermal stress fields and crack formation across the fabricated parts. The trend of the results reveals that by preheating the substrate prior to the fabrication process, it is possible to substantially reduce the formed micro-cracks. To demonstrate the feasibility of preheating on the reduction of micro-cracks, several simulations and experiments are performed in which a crack-free result is obtained, with a 22 per cent reduction in thermal stresses when the substrate is preheated to 800 K. The numerical and experimental results are also used to study the circumstances of the microstructural formation during the fabrication process. To conclude this research, the developed modelling approach is further extended to briefly discuss the effects of the path patterns and the main operating parameters on the outcomes of the process. The effects of the material properties and their variations on the temperature distributions and thermal stress fields are studied by fabrication of a thin wall of two Stellite 6 layers and two Ti layers on a stainless steel substrate.

The modeling of nuclear reactors involves the solution of a multi-physics problem with widely varying time and length scales. This translates mathematically to solving a system of coupled, non-linear, and stiff partial differential equations (PDEs). Multi-physics applications possess the added complexity that most of the solution fields participate in various physics components, potentially yielding spatial and/or temporal coupling errors. This dissertation deals with the verification aspects associated with such a multi-physics code, i.e., the substantiation that the mathematical description of the multi-physics equations are solved correctly (both in time and space). Conventional paradigms used in reactor analysis problems employed to couple various physics components are often non-iterative and can be inconsistent in their treatment of the non-linear terms. This leads to the usage of smaller time steps to maintain stability and accuracy requirements, thereby increasing the overall computational time for simulation. The inconsistencies of these weakly coupled solution methods can be overcome using tighter coupling strategies and yield a better approximation to the coupled non-linear operator, by resolving the dominant spatial and temporal scales involved in the multi-physics simulation. A multi-physics framework, KARMA (K(c)ode for Analysis of Reactor and other Multi-physics Applications), is presented. KARMA uses tight coupling strategies for various physical models based on a Matrix-free Nonlinear-Krylov (MFNK) framework in order to attain high-order spatio-temporal accuracy for all solution fields in amenable wall clock times, for various test problems. The framework also utilizes traditional loosely coupled methods as lower-order solvers, which serve as efficient preconditioners for the tightly coupled solution. Since the software platform employs both lower and higher-order coupling strategies, it can easily be used to test and evaluate different coupling strategies and numerical methods and to compare their efficiency for problems of interest. Multi-physics code verification efforts pertaining to reactor applications are described and associated numerical results obtained using the developed multi-physics framework are provided. The versatility of numerical methods used here for coupled problems and feasibility of general non-linear solvers with appropriate physics-based preconditioners in the KARMA framework offer significantly efficient techniques to solve multi-physics problems in reactor analysis.