A Language-centered Approach to support environmental modeling with Cellular Automata

Die Anwendung von Methodiken und Technologien aus dem Bereich der Softwaretechnik auf den Bereich der Umweltmodellierung ist eine gemeinhin akzeptierte Vorgehensweise. Im Rahmen der "modellgetriebenen Entwicklung"(MDE, model-driven engineering) werden Technologien entwickelt, die darauf abzielen, Softwaresysteme vorwiegend auf Basis von im Vergleich zu Programmquelltexten relativ abstrakten Modellen zu entwickeln. Ein wesentlicher Bestandteil von MDE sind Techniken zur effizienten Entwicklung von "domänenspezifischen Sprachen"( DSL, domain-specific language), die auf Sprachmetamodellen beruhen. Die vorliegende Arbeit zeigt, wie modellgetriebene Entwicklung, und insbesondere die metamodellbasierte Beschreibung von DSLs, darüber hinaus Aspekte der Pragmatik unterstützen kann, deren Relevanz im erkenntnistheoretischen und kognitiven Hintergrund wissenschaftlichen Forschens begründet wird. Hierzu wird vor dem Hintergrund der Erkenntnisse des "modellbasierten Forschens"(model-based science und model-based reasoning) gezeigt, wie insbesondere durch Metamodelle beschriebene DSLs Möglichkeiten bieten, entsprechende pragmatische Aspekte besonders zu berücksichtigen, indem sie als Werkzeug zur Erkenntnisgewinnung aufgefasst werden. Dies ist v.a. im Kontext großer Unsicherheiten, wie sie für weite Teile der Umweltmodellierung charakterisierend sind, von grundsätzlicher Bedeutung. Die Formulierung eines sprachzentrierten Ansatzes (LCA, language-centered approach) für die Werkzeugunterstützung konkretisiert die genannten Aspekte und bildet die Basis für eine beispielhafte Implementierung eines Werkzeuges mit einer DSL für die Beschreibung von Zellulären Automaten (ZA) für die Umweltmodellierung. Anwendungsfälle belegen die Verwendbarkeit von ECAL und der entsprechenden metamodellbasierten Werkzeugimplementierung.The application of methods and technologies of software engineering to environmental modeling and simulation (EMS) is common, since both areas share basic issues of software development and digital simulation. Recent developments within the context of "Model-driven Engineering" (MDE) aim at supporting the development of software systems at the base of relatively abstract models as opposed to programming language code. A basic ingredient of MDE is the development of methods that allow the efficient development of "domain-specific languages" (DSL), in particular at the base of language metamodels. This thesis shows how MDE and language metamodeling in particular, may support pragmatic aspects that reflect epistemic and cognitive aspects of scientific investigations. For this, DSLs and language metamodeling in particular are set into the context of "model-based science" and "model-based reasoning". It is shown that the specific properties of metamodel-based DSLs may be used to support those properties, in particular transparency, which are of particular relevance against the background of uncertainty, that is a characterizing property of EMS. The findings are the base for the formulation of an corresponding specific metamodel- based approach for the provision of modeling tools for EMS (Language-centered Approach, LCA), which has been implemented (modeling tool ECA-EMS), including a new DSL for CA modeling for EMS (ECAL). At the base of this implementation, the applicability of this approach is shown

Toward Accessible Multilevel Modeling in Systems Biology: A Rule-based Language Concept

Promoted by advanced experimental techniques for obtaining high-quality data and the steadily accumulating knowledge about the complexity of life, modeling biological systems at multiple interrelated levels of organization attracts more and more attention recently. Current approaches for modeling multilevel systems typically lack an accessible formal modeling language or have major limitations with respect to expressiveness. The aim of this thesis is to provide a comprehensive discussion on associated problems and needs and to propose a concrete solution addressing them

Simulation Modelling of Distributed-Shared Memory Multiprocessors

Institute for Computing Systems ArchitectureDistributed shared memory (DSM) systems have been recognised as a compelling platform for parallel computing due to the programming advantages and scalability. DSM systems allow applications to access data in a logically shared address space by abstracting away the distinction of physical memory location. As the location of data is transparent, the sources of overhead caused by accessing the distant memories are difficult to analyse. This memory locality problem has been identified as crucial to DSM performance. Many researchers have investigated the problem using simulation as a tool for conducting experiments resulting in the progressive evolution of DSM systems. Nevertheless, both the diversity of architectural configurations and the rapid advance of DSM implementations impose constraints on simulation model designs in two issues: the limitation of the simulation framework on model extensibility and the lack of verification applicability during a simulation run causing the delay in verification process. This thesis studies simulation modelling techniques for memory locality analysis of various DSM systems implemented on top of a cluster of symmetric multiprocessors. The thesis presents a simulation technique to promote model extensibility and proposes a technique for verification applicability, called a Specification-based Parameter Model Interaction (SPMI). The proposed techniques have been implemented in a new interpretation-driven simulation called DSiMCLUSTER on top of a discrete event simulation (DES) engine known as HASE. Experiments have been conducted to determine which factors are most influential on the degree of locality and to determine the possibility to maximise the stability of performance. DSiMCLUSTER has been validated against a SunFire 15K server and has achieved similarity of cache miss results, an average of +-6% with the worst case less than 15% of difference. These results confirm that the techniques used in developing the DSiMCLUSTER can contribute ways to achieve both (a) a highly extensible simulation framework to keep up with the ongoing innovation of the DSM architecture, and (b) the verification applicability resulting in an efficient framework for memory analysis experiments on DSM architecture

Modélisation de Systèmes Complexes par Composition : Une démarche hiérarchique pour la co-simulation de composants hétérogènes

This work deals with complex system Modeling and Simulation (M&S). The particularity of such systems is the numerous heterogeneous entities in interaction involved inside them. This particularity leads to several organization layers and scientific domains. As a consequence, their study requests many perspectives (different temporal and spatial scales, different domains and formalisms, different granularities...). The challenge is the rigorous integration of these various system perspectives inside an M&S process. In other words, the difficulty is to define successive steps to follow in order to integrate several points of view inside the same model. Multi-modeling and co-simulation are promising approaches to do so. The underlying problem is to define a modular and hierarchical process fitted with a rigorous way to integrate heterogeneous components and which is supported by a software environment that covers the whole M&S cycle.MECSYCO (Multi-agent Environment for Complex SYstem CO-simulation) is a co-simulation middleware focusing on the reuse of existing models from other software. It relies on a software and formal DEVS-based wrapping, provides heterogeneity handling mechanisms and ensures a decentralized and modular co-simulation. MECSYCO deals with the heterogeneous component integration need but its M&S process does not have all the properties above-mentioned. Notably, the hierarchical modeling ability is missing.To overcome this, we propose to fit MECSYCO with a descriptive multi-modeling and co-simulation process that allows the hierarchical design of multi-models using models from other software. Our process is split into three steps: the atomic model integration, the composition (hierarchical multi-model construction) and finally the experimentation. We adopt a descriptive approach where a description file is linked to each product of these steps, these documents enable to manipulate them.The use of description files completes the integration steps, allows a hierarchical and modular multi-model design and isolates the experiments.Then we set up a development environment based on Domain Specific Languages (DSL) to support the description work, and we automate the transition from an experiment description to its effective co-simulation. This is a Model-Driven Engineering approach which allows us to put into practice our contribution by facilitating the modelers' work and by avoiding implementation mistakes.Our contribution fits MECSYCO with the hierarchical design property and with a DSL-based M&S environment while keeping its rigorous integration process and its modularity. Our work is evaluated on two examples. The first one renews a hybrid highway multi-model already implemented in MECSYCO, it shows the conservation of the middleware former properties. The second one is a simple thermal smart-building multi-model which highlights the incremental design of a multi-model and the integration of new components while putting our entire approach into practice.Le contexte de ce travail est la modélisation et simulation (M&S) de systèmes complexes. Ces systèmes se caractérisent par un grand nombre d'entités hétérogènes en interaction faisant apparaitre plusieurs niveaux d'organisation et plusieurs domaines. Leur étude nécessite de combiner plusieurs points de vue (différentes échelles temporelles et spatiales, différents domaines scientifiques et formalismes, différents niveaux de résolution...).Le challenge est l'intégration rigoureuse de ces différents points de vue sur un système au sein d'une démarche de M&S. Dit autrement, le défi est de définir une marche à suivre permettant d'intégrer plusieurs perspectives au sein d'un même modèle. La multi-modélisation et la co-simulation sont deux approches prometteuses pour cela. La difficulté sous-jacente est de fournir une démarche de M&S modulaire, hiérarchique, dotée d'une approche d'intégration de composants hétérogènes rigoureuse et associée à un environnement logiciel supportant l'ensemble du cycle de M&S pour la mettre en pratique.MECSYCO (Multi-agent Environment for Complex SYstem CO-simulation) est un intergiciel de co-simulation se focalisant sur la réutilisation de modèles issus d'autres logiciels. Il se base sur une stratégie d'encapsulation logicielle et formelle fondée sur DEVS, fournit des mécanismes de gestion des hétérogénéités, et assure une co-simulation décentralisée et modulaire. MECSYCO répond au besoin d'intégration de composants hétérogènes au sein d'une co-simulation, mais ne propose pas de démarche complète comprenant l'ensemble des propriétés énoncées précédemment. Il manque notamment la possibilité de hiérarchiser. Pour pallier à ce manque, dans la continuité des travaux sur MECSYCO nous proposons une démarche de multi-modélisation et co-simulation descriptive autorisant la construction incrémentale de multi-modèles à partir de modèles issus d'autres logiciels. Notre démarche est décomposée en trois étapes : l'intégration des modèles atomiques, la composition (création hiérarchique du multi-modèle) et enfin l'expérimentation. Nous adoptons une approche descriptive où chaque élément produit lors de ces étapes est associé à une description permettant de le manipuler. L'utilisation des descriptions complète le processus d'intégration, permet la construction incrémentale et modulaire des multi-modèles, et isole l'expérimentation. Nous mettons ensuite en place un environnement de développement basé sur des langages dédiés aux descriptions, et nous automatisons le passage d'une description d'expérience à sa co-simulation effective. C'est une démarche d'Ingénierie Dirigée par les Modèles qui nous permet de mettre en pratique notre approche en facilitant le travail des modélisateurs et en évitant les erreurs d'implémentation.Nous apportons à MECSYCO la propriété de hiérarchisation et un environnement de développement tout en conservant l'intégration rigoureuse et la modularité. Nous évaluons notre contribution sur deux exemples. Le premier reprend un multi-modèle d'autoroute hybride implémenté dans MECSYCO, il montre la conservation des propriétés d'intégration. Le second est un multi-modèle simple de thermique de bâtiment intelligent, il illustre la construction incrémentale d'un multi-modèle et l'intégration de nouveaux composants tout en mettant en pratique l'ensemble de notre démarche

Fifth Conference on Artificial Intelligence for Space Applications

The Fifth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: automation for Space Station; intelligent control, testing, and fault diagnosis; robotics and vision; planning and scheduling; simulation, modeling, and tutoring; development tools and automatic programming; knowledge representation and acquisition; and knowledge base/data base integration

Programmiersprachen und Rechenkonzepte

Seit 1984 veranstaltet die GI--Fachgruppe 2.1.4 "Programmiersprachen und Rechenkonzepte", die aus den ehemaligen Fachgruppen 2.1.3 "Implementierung von Programmiersprachen" und 2.1.4 "Alternative Konzepte für Sprachen und Rechner" hervorgegangen ist, regelmäßi g im Frühjahr einen Workshop im Physikzentrum Bad Honnef. Das Treffen dient in erster Linie dem gegenseitigen Kennenlernen, dem Erfahrungsaustausch, der Diskussion und der Vertiefung gegenseitiger Kontakte

Simulations of nanoscale spatial disorder

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 125-127).In this thesis, we detail the design, implementation, and testing of two simulations of nanometer scale disorder phenomena important for electronic device fabrication. We created a kinetic simulator for the surface assembly of quantum dots into ordered or disordered monolayers. We utilized a platform for high-precision motion and collision resolution and implemented the behavior of quantum dots on a surface. The simulation demonstrated experimentally observed behavior and offers insights into future device design. We also created a material simulation of the electrochemical oxidation of a metal surface with nanoscale roughness. We demonstrated that by preserving the amount of metal and making the oxide coating conformal, anodization can highly planarize the metal surface. We verify the convergence of our results as we increase the accuracy of our model. We demonstrate differences in the rate of planarization between additive and subtractive surface features which could not be observed by experiment and make predictions about the planarization of metals with different oxide expansion coefficients.by Ethan Gabriel Grief Howe.M.Eng

Global Qualitative Flow-Path Modeling for Local State Determination in Simulation and Analysis

For qualitative modeling and analysis, a general qualitative abstraction of power transmission variables (flow and effort) for elements of flow paths includes information on resistance, net flow, permissible directions of flow, and qualitative potential is discussed. Each type of component model has flow-related variables and an associated internal flow map, connected into an overall flow network of the system. For storage devices, the implicit power transfer to the environment is represented by "virtual" circuits that include an environmental junction. A heterogeneous aggregation method simplifies the path structure. A method determines global flow-path changes during dynamic simulation and analysis, and identifies corresponding local flow state changes that are effects of global configuration changes. Flow-path determination is triggered by any change in a flow-related device variable in a simulation or analysis. Components (path elements) that may be affected are identified, and flow-related attributes favoring flow in the two possible directions are collected for each of them. Next, flow-related attributes are determined for each affected path element, based on possibly conflicting indications of flow direction. Spurious qualitative ambiguities are minimized by using relative magnitudes and permissible directions of flow, and by favoring flow sources over effort sources when comparing flow tendencies. The results are output to local flow states of affected components