Transiente Simulationen im Rahmen von Parameterstudien oder Optimierungsprozessen erfor-dern die Anwendung der Modellordnungsreduktion zur Minimierung der Berechnungs¬zeiten. Die aus der Wärmestrahlung resultierende Nichtlinearität bei der Analyse thermischer Felder wird hier als äußere Last betrachtet, wodurch die entkoppelte Ermittlung der strahlungs-beding¬ten Wärmeströme gelingt. Darüber hinaus ermöglichen die infolgedessen konstanten System¬matrizen die Reduktion des Temperaturvektors mit etablierten Verfahren für lineare Systeme, wie beispielsweise den Krylov-Unterraummethoden. Die aus der in der Regel großflächigen Verteilung der thermischen Lasten folgende hohe Anzahl von Systemeingängen limitiert allerdings die erzielbare reduzierte Dimension. Deshalb werden zustandsunabhängige, sich synchron verändernde Lasten zu einem Eingang zusammengefasst. Die aus der Strahlung resultierenden Wärmeströme sind im Gegensatz dazu durch die aktuelle Temperaturverteilung bestimmt und lassen sich nicht derart gruppieren. Vor diesem Hintergrund wird ein Ansatz basierend auf der Singulärwertzerlegung von aus Trai¬ningssimulationen gewonnenen Beispiellastvektoren vorgeschlagen. Auf diese Weise gelingt eine erhebliche Verringerung der Eingangsanzahl, sodass im reduzierten System ein sehr geringer Freiheitsgrad erreicht wird. Im Vergleich zur Proper Orthogonal Decomposition (POD) genügen dabei deutlich weniger Trainingsdaten, was den Rechenaufwand während der Offline-Phase erheblich vermindert. Darüber hinaus dehnt das entwickelte Verfahren die Gültigkeit des reduzierten Modells auf einen weiten Parameterbereich aus. Die Berechnung der strahlungsbedingten Wärmeströme in der Ausgangsdimension bestimmt dann den numerischen Aufwand. Mit der Discrete Empirical Interpolation Method (DEIM) wird die Auswertung der Nichtlinearität auf ausgewählte Modellknoten beschränkt. Schließlich erlaubt die Anwendung der POD auf die Wärmestrahlungsbilanz die schnelle Anpassung des Emissionsgrades. Somit hängt das reduzierte System nicht mehr vom ursprünglichen Freiheitsgrad ab und die Gesamt-simulationszeit verkürzt sich um mehrere Größenordnungen. / Transient simulations as part of parameter studies or optimization processes require the appli-cation of model order reduction to minimize computation times. Nonlinearity resulting from heat radiation in thermal analyses is considered here as an external load. Thereby, the determi-nation of the radiation-induced heat flows is decoupled from the temperature equation. Hence, the system matrices become invariant and established algorithms for linear systems, such as Krylov Subspace Methods, can be used for the reduction of the temperature vector. However, in general the achievable reduced dimension is limited as the thermal loads distributed over large parts of the surface lead to a high number of system inputs. Therefore, state-independent, synchronously changing loads are combined into one input. In contrast, the heat flows resulting from radiation are determined by the current temperature distribution and cannot be grouped in this way. Against this background, an approach based on the singular value decomposition of snapshots obtained from training simulations is proposed allowing a considerable decreased input number and a very low degree of freedom in the reduced system. Compared to Proper Orthogonal Decomposition (POD), significantly less training data is required reducing the computational costs during the offline phase. In addition, the developed method extends the validity of the reduced model to a wide parameter range. The computation of the radiation-induced heat flows, which is performed in the original dimension, then determines the numerical effort. The Discrete Empirical Interpolation Method (DEIM) restricts the evaluation of the nonlinearity to selected model nodes. Finally, the application of the POD to the heat radiation equation enables a rapid adjustment of the emissivity. Thus, the reduced system is no longer dependent on the original degree of freedom and the total simulation time is shortened by several orders of magnitude.

Für die elastische Mehrkörpersimulation bzw. die FEM-MKS-Kopplung sind reduzierte FE-Modelle von großer Bedeutung. Die Erstellung reduzierter Modelle mit hoher Abbildungsgüte im Rahmen einer Modellordnungsreduktion erfordert einerseits ein geeignetes Reduktions-verfahren und andererseits zuverlässige Korrelationsmethoden. Beides wird durch die Soft-ware MORPACK bereitgestellt. Die Korrelation reduzierter FE-Modelle basiert in MORPACK derzeit ausschließlich auf modalen Eigenschaften. Ausgehend von der Annahme, dass sich die Abbildungsgüte eines reduzierten FE-Modells erst im Rahmen einer Zeitbereichssimula-tion vollständig beurteilen lässt, ist eine dahingehende Erweiterung von MORPACK geplant. Für einfache Topologien muss die Möglichkeit bestehen, das dynamische Verhalten, redu-zierter Modelle, direkt in MORPACK zu simulieren. Mit Hilfe der resultierenden Zeitsignale werden die reduzierten Modelle bewertet. Für die Umsetzung dieser Idee muss in MORPACK zunächst ein eigenständiges EMKS-Programm implementiert werden. Die Implementierung des EMKS-Programms in MORPACK (bzw. MATLAB) stellt den Schwerpunkt dieser Arbeit dar. Es werden zunächst die Anforderungen an das EMKS-Programm formuliert. Nach der Behandlung aller erforderlichen theoretischen Grundlagen werden die Systemgleichungen hergeleitet. Anschließend wird ein Formalismus bereitgestellt, der den Aufbau der Systemgleichungen, auf Basis der Nutzereingaben ermöglicht. Nach der Implementierung des Formalismus wird das EMKS-Programm verifiziert und erprobt.:1 Einleitung 1 1.1 Motivation 1 1.2 Zielsetzung 2 1.3 Lösungsweg 3 2 Verifikation und Optimierung durch Zeitbereichssimulationen 5 2.1 Erweiterung von MORPACK 5 2.2 Anforderungen an das EMKS-Programm 10 2.3 Korrelation von Zeitsignalen 12 3 Grundlagen der elastischen Mehrkörpersimulation 16 3.1 Berücksichtigung elastischer Deformationen in Mehrkörpersystemen 16 3.2 Kinematik freier Einzelkörper 19 3.2.1 Räumliche Drehungen von Bezugssystemen 19 3.2.2 Methode des bewegten Bezugssystems 23 3.2.3 Diskretisierung und Variablen für die Zustandsbeschreibung 25 3.2.4 Kinematik der Schnittstellenknoten 28 3.3 Kinetik freier Einzelkörper 31 3.4 Wahl des Körperbezugssystems 40 3.4.1 Kinematische Zwangsbedingungen 40 3.4.2 Kinetische Zwangsbedingungen 42 3.5 Gebundene Mehrkörpersysteme 44 3.6 Daten von elastischen Körpern 48 4 Bewegungsgleichungen und EMKS Formalismus für zwei beliebig gekoppelte Körper 52 4.1 Modellbildung 52 4.2 Bewegungsgleichungen in einem Satz natürlicher Koordinaten 54 4.3 Transformation auf Minimalkoordinaten 62 4.3.1 Formalismus 63 4.3.2 Herleitung der notwendigen Vektoren und Matrizen 65 5 Erweiterung des EMKS-Algorithmus für die festgelegte Topologie 76 6 Implementierung in MORPACK 84 6.1 Struktur der Eingabe- und Definitionsdaten 84 6.2 Grafische Benutzeroberfläche und Einbindung in MORPACK 90 6.3 Implementierung des EMKS-Formalismus 92 7 Verifikation und Erprobung 98 7.1 Verifikation mit SIMPACK 98 7.2 Erprobung der Prozesskette 101 7.2.1 Erprobungsmodell 101 7.2.2 Ergebnisse der Zeitbereichssimulation im Vergleich zu modalen Korrelationskriterien 103 7.2.3 Optimierung durch Zeitbereichssimulation 108 8 Zusammenfassung und Ausblick 112 / Reduced FE-Models are very important for elastic multibody simulation and FEM-MKS-coupling. The generation of reduced FE-models with high approximation quality in a model order reduction requires on the one hand a suitable reduction method and on the other hand reliable correlation methods. Both are provided by the MORPACK software. In MORPACK the correlation of reduced FE models based currently only on modal properties. An extension of the MORPACK software is planned on the assumption, that the approximation quality of a reduced FE-model can be completely assessed only in a time domain simulation. For simple topologies, it must be possible to simulate the dynamic behavior of reduced models directly into MORPACK. With the correlation of resulting time signals, the reduced models are as-sessed. To realize this idea, an independent EMKS program must be implemented in MORPACK. The implementation of the EMKS program in MORPACK (respectively MATLAB) represents the focus of this thesis. The first part is to formulate the necessary requirements for the EMKS program. After handling of all the necessary theoretical foundations, the system equa-tions are derived. Subsequently, formalism is provided that allows a construction of the sys-tem equations based on the user input. After the implementation of the formalism, the EMKS program will verify and tested.:1 Einleitung 1 1.1 Motivation 1 1.2 Zielsetzung 2 1.3 Lösungsweg 3 2 Verifikation und Optimierung durch Zeitbereichssimulationen 5 2.1 Erweiterung von MORPACK 5 2.2 Anforderungen an das EMKS-Programm 10 2.3 Korrelation von Zeitsignalen 12 3 Grundlagen der elastischen Mehrkörpersimulation 16 3.1 Berücksichtigung elastischer Deformationen in Mehrkörpersystemen 16 3.2 Kinematik freier Einzelkörper 19 3.2.1 Räumliche Drehungen von Bezugssystemen 19 3.2.2 Methode des bewegten Bezugssystems 23 3.2.3 Diskretisierung und Variablen für die Zustandsbeschreibung 25 3.2.4 Kinematik der Schnittstellenknoten 28 3.3 Kinetik freier Einzelkörper 31 3.4 Wahl des Körperbezugssystems 40 3.4.1 Kinematische Zwangsbedingungen 40 3.4.2 Kinetische Zwangsbedingungen 42 3.5 Gebundene Mehrkörpersysteme 44 3.6 Daten von elastischen Körpern 48 4 Bewegungsgleichungen und EMKS Formalismus für zwei beliebig gekoppelte Körper 52 4.1 Modellbildung 52 4.2 Bewegungsgleichungen in einem Satz natürlicher Koordinaten 54 4.3 Transformation auf Minimalkoordinaten 62 4.3.1 Formalismus 63 4.3.2 Herleitung der notwendigen Vektoren und Matrizen 65 5 Erweiterung des EMKS-Algorithmus für die festgelegte Topologie 76 6 Implementierung in MORPACK 84 6.1 Struktur der Eingabe- und Definitionsdaten 84 6.2 Grafische Benutzeroberfläche und Einbindung in MORPACK 90 6.3 Implementierung des EMKS-Formalismus 92 7 Verifikation und Erprobung 98 7.1 Verifikation mit SIMPACK 98 7.2 Erprobung der Prozesskette 101 7.2.1 Erprobungsmodell 101 7.2.2 Ergebnisse der Zeitbereichssimulation im Vergleich zu modalen Korrelationskriterien 103 7.2.3 Optimierung durch Zeitbereichssimulation 108 8 Zusammenfassung und Ausblick 112

Thermo-elastic errors are one of the main drivers for reduced quality of workpieces in machining. Cooling systems can prevent these errors and improve quality. The paper describes a simulation method that takes into account both the temperature field of a machine tool frame and the fluid cooling system. Such simulations can help to improve the thermal stability of the machine tool frame.

No description available.

付記する学位プログラム名: 京都大学卓越大学院プログラム「先端光・電子デバイス創成学」 / 京都大学 / 新制・課程博士 / 博士(工学) / 甲第25293号 / 工博第5252号 / 京都大学大学院工学研究科電気工学専攻 / (主査)教授 松尾 哲司, 教授 引原 隆士, 教授 土居 伸二 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Dans le domaine automobile, les modules électroniques de puissance des produits mécatroniques voient leur puissance sans cesse s'accroître, tout en étant confinés dans des volumes de plus en plus réduits. Au cours de leur fonctionnement, les composants semi-conducteurs et leur assemblage subissent ainsi des contraintes électro-thermo-mécaniques sévères, susceptibles d'entraîner leur destruction et de provoquer la défaillance du produit. L'étude de la fiabilité et le calcul de la durée de vie de tels produits dépendent des températures de jonction calculées au niveau des puces des composants de puissances. De surcroît, le contexte d'applications embarquées requiert de maîtriser, outre les paramètres électriques et mécaniques, les paramètres thermiques tels que les températures de jonctions et les puissances dissipées au niveau des composants, qu'il est nécessaire de réguler et contrôler en temps réel afin d'assurer le bon fonctionnement du produit. L'objectif de cette thèse est ainsi de proposer une méthode d'identification de modèles réduits dans le but d'estimer le comportement thermique des modules électroniques de puissance, en se fondant uniquement sur les données d'entrées et les résultats issus d'une simulation numérique d'un modèle détaillé du système étudié. Dans cette thèse, une nouvelle méthode d'identification, nommée « Kernel Identification Method », est développée. Cette méthode a été validée sur une application industrielle traitant d'un problème thermique couplé solide/fluide dont le comportement est essentiellement régi par de la convection forcée. Une étude exploratoire portant sur l'identification de problèmes non linéaires où la convection naturelle joue le rôle dominant est ensuite proposée. A cet effet, deux méthodes d’identification non-paramétrique sont proposées : (i) une première méthode basée sur l’extension de la méthode Kernel Identification Method ; et (ii) une deuxième méthode basée sur la variante dite « Unscented » du filtre de Kalman. / In automotive applications, the thermal dissipation of power electronics modules in mechatronic products is constantly increasing, whereas these products are confined in increasingly reduced volumes. During their operation, the semiconductor components and their environment are then submitted to severe electro-thermo-mechanical stresses that could cause their damage and lead to the product failure. The reliability and lifetime prevision of such products depend on the temperature junction located at the chip of power components. Furthermore, in order to ensure the safe operation of embedded applications, it is essential to perform a real-time control of thermal parameters such as the junction temperatures and power dissipated on the power components, in addition to the electrical and mechanical parameters. The objective of this thesis is to develop an identification method aimed at producing reduced thermal models to estimate the thermal behaviour of power electronic modules. Designed in a non-intrusive framework, this method post-processes the input data and the results produced by the numerical simulation of a detailed of the system under study. In this thesis, a new identification method, called "Kernel Identification Method" is developed. It has been validated on an industrial application dealing with a thermally coupled solid / fluid problem mainly governed by forced convection. An exploratory study of nonlinear problems identification where the natural convection plays the dominant role is then proposed. To this end, two identification methods of nonparametric nature are proposed: (i) a method based on the extension of the Kernel Identification Method; and (ii) a second method based on the "unscented" variant of the Kalman filter.

Nous présentons dans cette thèse nos travaux sur la réduction d'ordre appliquée à des simulations d'aérothermie. Nous considérons le couplage entre les équations de Navier-Stokes et une équations d'énergie de type advection-diffusion. Les paramètres physiques considérés nous obligent à considéré l'introduction d'opérateurs de stabilisation de type SUPG ou GLS. Le but étant d'ajouter une diffusion numérique dans la direction du champs de convection, afin de supprimer les oscillations non-phyisques. Nous présentons également notre stratégie de résolution basée sur la méthode des bases réduite (RBM). Afin de retrouver une décomposition affine, essentielle pour l'application de la RBM, nous avons implémenté une version discrète de la méthode d'interpolation empirique (EIM). Cette variante permet de la construction d'approximation affine pour des opérateurs complexes. Nous utilisons notamment cette méthode pour la réduction des opérateurs de stabilisations. Cependant, la construction des bases EIM pour des problèmes non-linéaires implique un grand nombre de résolution éléments finis. Pour pallier à ce problème, nous mettons en oeuvre les récents développement de l'algorithme de coconstruction entre EIM et RBM (SER). / We present in this thesis our work on model order reduction for aerothermal simulations. We consider the coupling between the incompressible Navier-Stokes equations and an advection-diffusion equation for the temperature. Since the physical parameters induce high Reynolds and Peclet numbers, we have to introduce stabilization operators in the formulation to deal with the well known numerical stability issue. The chosen stabilization, applied to both fluid and heat equations, is the usual Streamline-Upwind/Petrov-Galerkin (SUPG) which add artificial diffusivity in the direction of the convection field. We also introduce our order reduction strategy for this model, based on the Reduced Basis Method (RBM). To recover an affine decomposition for this complex model, we implemented a discrete variation of the Empirical Interpolation Method (EIM) which is a discrete version of the original EIM. This variant allows building an approximated affine decomposition for complex operators such as in the case of SUPG. We also use this method for the non-linear operators induced by the shock capturing method. The construction of an EIM basis for non-linear operators involves a potentially huge number of non-linear FEM resolutions - depending on the size of the sampling. Even if this basis is built during an offline phase, we usually can not afford such expensive computational cost. We took advantage of the recent development of the Simultaneous EIM Reduced basis algorithm (SER) to tackle this issue.

O objetivo deste estudo é apresentar uma revisão sobre técnicas de redução da ordem de modelos dinâmicos lineares e invariantes no tempo. Com a implementação de tais técnicas, o autor mostra que é possível reproduzir as principais características da resposta de um modelo de alta ordem através de um modelo de ordem reduzida com menor número de graus de liberdade. Uma metodologia para redução da ordem de modelos de sistemas dinâmicos foi apresentada. Os processos envolvidos nesta metodologia foram descritos, os quais são: técnicas para realizar projeções do sistema em diferentes bases, selecionar os graus de liberdade que são bons candidatos a eliminação, eliminar graus de liberdade do modelo completo e implementar correções na resposta do modelo reduzido. Foram apresentadas maneiras de quantificar as similitudes entre as respostas dos modelos completo e reduzido através de métricas de representatividade. Para implementar e estudar as técnicas de redução apresentadas, o autor elaborou dois modelos para estudo de caso: um modelo para estudo da dinâmica vertical de um veículo de passeio e outro modelo para estudo da dinâmica longitudinal de um trem. Diferentes técnicas de redução foram implementadas a partir dos dois modelos para estudo de caso e os resultados foram comparados através das métricas de representatividade. O critério proposto pelo autor para quantificar desempenho de um modelo reduzido foi utilizado para determinar de maneira objetiva o modelo reduzido mais adequado para cada aplicação. Como contribuição neste trabalho, o autor propôs uma definição de desempenho de um modelo reduzido e um método para quantificar o mesmo, além de duas novas métricas para mensurar a capacidade do modelo reduzido em reproduzir os máximos sobre-sinais e tempos de acomodação do modelo completo. / The objective of this work is to present a revision about model order reduction techniques applied to linear, time invariant dynamic systems. With the implementation of these techniques, the author shows that it is possible to reproduce the main characteristics of the response of a high order dynamic system using a reduced order model with fewer degrees of freedom. A model order reduction methodology was presented. The processes which are involved in this methodology were described, which are: techniques for projection onto different basis, selection of the most suitable degrees of freedom to be reduced, elimination of degrees of freedom from the high order model, implementation of corrections at the reduced model response. The author showed ways to quantify the similarities between the responses of the complete and reduced models using representativeness metrics. In order to implement and study the presented model order reduction techniques, the author developed two case study models: one model to study the vertical dynamics of a passenger car and another model to study the longitudinal dynamics of a train. Different model order reduction techniques were implemented and its results were compared using representativeness metrics and the performance of the reduced models. The criteria proposed by the author to quantify the performance of a reduced order model was used to objectively determine the most suitable reduced order model for each application. The author proposed, as contribution at this work, a definition of the reduced order model performance, a method to quantify its performance and two new metrics to measure the capacity of the reduced model to reproduce the overshoots and settling times of the complete model.

The continuous miniaturization of electronic systems using the three-dimensional (3D) integration technique has brought in new challenges for the computer-aided design and modeling of 3D integrated circuits (ICs) and systems. The major challenges for the modeling and analysis of 3D integrated systems mainly stem from four aspects: (a) the interaction between the electrical and thermal domains in an integrated system, (b) the increasing modeling complexity arising from 3D systems requires the development of multiscale techniques for the modeling and analysis of DC voltage drop, thermal gradients, and electromagnetic behaviors, (c) efficient modeling of microfluidic cooling, and (d) the demand of performing fast thermal simulation with varying design parameters. Addressing these challenges for the electrical/thermal modeling and analysis of 3D systems necessitates the development of novel numerical modeling methods. This dissertation mainly focuses on developing efficient electrical and thermal numerical modeling and co-simulation methods for 3D integrated systems. The developed numerical methods can be classified into three categories. The first category aims to investigate the interaction between electrical and thermal characteristics for power delivery networks (PDNs) in steady state and the thermal effect on characteristics of through-silicon via (TSV) arrays at high frequencies. The steady-state electrical-thermal interaction for PDNs is addressed by developing a voltage drop-thermal co-simulation method while the thermal effect on TSV characteristics is studied by proposing a thermal-electrical analysis approach for TSV arrays. The second category of numerical methods focuses on developing multiscale modeling approaches for the voltage drop and thermal analysis. A multiscale modeling method based on the finite-element non-conformal domain decomposition technique has been developed for the voltage drop and thermal analysis of 3D systems. The proposed method allows the modeling of a 3D multiscale system using independent mesh grids in sub-domains. As a result, the system unknowns can be greatly reduced. In addition, to improve the simulation efficiency, the cascadic multigrid solving approach has been adopted for the voltage drop-thermal co-simulation with a large number of unknowns. The focus of the last category is to develop fast thermal simulation methods using compact models and model order reduction (MOR). To overcome the computational cost using the computational fluid dynamics simulation, a finite-volume compact thermal model has been developed for the microchannel-based fluidic cooling. This compact thermal model enables the fast thermal simulation of 3D ICs with a large number of microchannels for early-stage design. In addition, a system-level thermal modeling method using domain decomposition and model order reduction is developed for both the steady-state and transient thermal analysis. The proposed approach can efficiently support thermal modeling with varying design parameters without using parameterized MOR techniques.

O objetivo deste estudo é apresentar uma revisão sobre técnicas de redução da ordem de modelos dinâmicos lineares e invariantes no tempo. Com a implementação de tais técnicas, o autor mostra que é possível reproduzir as principais características da resposta de um modelo de alta ordem através de um modelo de ordem reduzida com menor número de graus de liberdade. Uma metodologia para redução da ordem de modelos de sistemas dinâmicos foi apresentada. Os processos envolvidos nesta metodologia foram descritos, os quais são: técnicas para realizar projeções do sistema em diferentes bases, selecionar os graus de liberdade que são bons candidatos a eliminação, eliminar graus de liberdade do modelo completo e implementar correções na resposta do modelo reduzido. Foram apresentadas maneiras de quantificar as similitudes entre as respostas dos modelos completo e reduzido através de métricas de representatividade. Para implementar e estudar as técnicas de redução apresentadas, o autor elaborou dois modelos para estudo de caso: um modelo para estudo da dinâmica vertical de um veículo de passeio e outro modelo para estudo da dinâmica longitudinal de um trem. Diferentes técnicas de redução foram implementadas a partir dos dois modelos para estudo de caso e os resultados foram comparados através das métricas de representatividade. O critério proposto pelo autor para quantificar desempenho de um modelo reduzido foi utilizado para determinar de maneira objetiva o modelo reduzido mais adequado para cada aplicação. Como contribuição neste trabalho, o autor propôs uma definição de desempenho de um modelo reduzido e um método para quantificar o mesmo, além de duas novas métricas para mensurar a capacidade do modelo reduzido em reproduzir os máximos sobre-sinais e tempos de acomodação do modelo completo. / The objective of this work is to present a revision about model order reduction techniques applied to linear, time invariant dynamic systems. With the implementation of these techniques, the author shows that it is possible to reproduce the main characteristics of the response of a high order dynamic system using a reduced order model with fewer degrees of freedom. A model order reduction methodology was presented. The processes which are involved in this methodology were described, which are: techniques for projection onto different basis, selection of the most suitable degrees of freedom to be reduced, elimination of degrees of freedom from the high order model, implementation of corrections at the reduced model response. The author showed ways to quantify the similarities between the responses of the complete and reduced models using representativeness metrics. In order to implement and study the presented model order reduction techniques, the author developed two case study models: one model to study the vertical dynamics of a passenger car and another model to study the longitudinal dynamics of a train. Different model order reduction techniques were implemented and its results were compared using representativeness metrics and the performance of the reduced models. The criteria proposed by the author to quantify the performance of a reduced order model was used to objectively determine the most suitable reduced order model for each application. The author proposed, as contribution at this work, a definition of the reduced order model performance, a method to quantify its performance and two new metrics to measure the capacity of the reduced model to reproduce the overshoots and settling times of the complete model.