A proposta do trabalho é criar um modelo de simulação híbrida capaz de representar um sistema logístico. Partindo de uma investigação bibliográfica conceitual das metodologias de simulação de eventos discretos e da metodologia de simulação contínua (System Dynamics) capaz de revelar suas características principais e seus potenciais de aplicabilidade, é possível delinear as possibilidades de contribuição de ambas as metodologias para o desenvolvimento de modelos híbridos (metodologias discreta + contínua) de simulação. O modelo híbrido é desenvolvido sob a plataforma AnyLogic, e a integração adequada de ambas as metodologias no modelo criado é capaz de expandir o espectro de compreensão do sistema, com a possibilidade de integração de aspectos físicos e dimensionais a aspectos políticos e comportamentais do sistema em estudo, apresentando-se como ferramenta poderosa para sobrevivência às exigentes demandas concorrenciais. / This study aims at creating a hybrid simulation model able to properly represent a logistics system. Departing from a conceptual literature review about the discrete-event and the continuous (System Dynamics) simulation methodologies able to reveals its main features and potential of applicability, it is possible to define the possibilities of developing hybrid (discrete + continuous) simulation models. The proper integration of both methodologies in a hybrid model allows the expansion of the comprehension spectrum of the system, with the possibility of integrating the physical and dimensional aspects to political and behavior patterns, revealing the hybrid methodology as a powerful tool to succeed in the highly demanding business world.

A car with underinflated tires can lead to both safety and environmental issues. To combat this, markets have begun requiring new cars to feature a Tire Pressure Monitoring System. Systems without pressure sensors are referred to as indirect Tire Pressure Monitoring Systems, often utilizing wheel speed sensors in combination with other available sensor information to detect tire pressure losses.  NIRA Dynamics is a company founded in Linköping, Sweden, most known for its indirect Tire Pressure Monitoring System called TPI. TPI needs to be verified in a large number of scenarios, which may be both difficult and expensive to realize in real vehicle tests. The purpose of this master thesis was to investigate and model what physical phenomena are associated with having a trailer connected to a car, relevant for TPI. The goal was to construct a hybrid simulation framework, making it possible to modify car-only data to reflect the effects of having a trailer connected.  A car-trailer model was developed, showing close resemblance in simulations to real collected car-trailer sensor data. The model was then used to design a hybrid simulation framework, where car-only sensor signals were modified to mimic having different types of trailers attached. The hybrid simulation results show close resemblance to real collected trailer sensor data. By not requiring real trailer data for every scenario to evaluate software performance on, the proposed framework opens up the possibility to simulate data from a much larger number of trailer combinations than would otherwise have been feasible to test in real vehicle tests.

Computer designers rely upon near-cycle-accurate microarchitectural simulation to explore the design space of new systems. Unfortunately, such simulators are becoming increasingly slow as systems become more complex. Hybrid simulators which offload some of the simulation work onto FPGAs can increase the speed; however, such simulators must be automatically synthesized or the time to design them becomes prohibitive. Furthermore, FPGA implementations of simulators may require multiple FPGA clock cycles to implement behavior that takes place within one simulated clock cycle, making correct arbitrary composition of simulator components impossible and limiting the amount of hardware concurrency which can be achieved. Latency-Insensitive Bounded Dataflow Networks (LI-BDNs) have been suggested as a means to permit composition of simulator components in FPGAs. However, previous work has required that LI-BDNs be created manually. This paper introduces techniques for automated synthesis of LI-BDNs from the processes of a System-C microarchitectural model. We demonstrate that LI-BDNs can be successfully synthesized. We also introduce a technique for reducing the overhead of LI-BDNs when the latency-insensitive property is unnecessary, resulting in up to a 60% reduction in FPGA resource requirements.

INCOSE defines Model-Based Systems Engineering (MBSE) as "the formalized application of modeling to support system requirements, design, analysis, verification, and validation activities beginning in the conceptual design phase and continuing throughout development and later life cycle phases." One very important development is the utilization of MBSE to develop distributed and hybrid (discrete-continuous) simulation modeling systems. MBSE can help to describe the systems to be modeled and help make the right decisions and partitions to tame complexity. The ability to embrace conceptual modeling and interoperability techniques during systems specification and design presents a great advantage in distributed and hybrid simulation systems development efforts. Our research is aimed at the definition of a methodological framework that uses MBSE languages, methods and tools for the development of these simulation systems. A model-based composition approach is defined at the initial steps to identify distributed systems interoperability requirements and hybrid simulation systems characteristics. Guidelines are developed to adopt simulation interoperability standards and conceptual modeling techniques using MBSE methods and tools. Domain specific system complexity and behavior can be captured with model-based approaches during the system architecture and functional design requirements definition. MBSE can allow simulation engineers to formally model different aspects of a problem ranging from architectures to corresponding behavioral analysis, to functional decompositions and user requirements (Jobe, 2008).

Currently the network centric operation and network centric warfare have generated a new area of research focused on determining how hierarchical organizations composed by human beings and machines make decisions over collaborative environments. One of the most stressful scenarios for these kinds of organizations is the so-called extreme events. This dissertation provides a hybrid simulation methodology based on classical simulation paradigms combined with social network analysis for evaluating and improving the organizational structures and procedures, mainly the incident command systems and plans for facing those extreme events. According to this, we provide a methodology for generating hypotheses and afterwards testing organizational procedures either in real training systems or simulation models with validated data. As long as the organization changes their dyadic relationships dynamically over time, we propose to capture the longitudinal digraph in time and analyze it by means of its adjacency matrix. Thus, by using an object oriented approach, three domains are proposed for better understanding the performance and the surrounding environment of an emergency management organization. System dynamics is used for modeling the critical infrastructure linked to the warning alerts of a given organization at federal, state and local levels. Discrete simulations based on the defined concept of "community of state" enables us to control the complete model. Discrete event simulation allows us to create entities that represent the data and resource flows within the organization. We propose that cognitive models might well be suited in our methodology. For instance, we show how the team performance decays in time, according to the Yerkes-Dodson curve, affecting the measures of performance of the whole organizational system. Accordingly we suggest that the hybrid model could be applied to other types of organizations, such as military peacekeeping operations and joint task forces. Along with providing insight about organizations, the methodology supports the analysis of the "after action review" (AAR), based on collection of data obtained from the command and control systems or the so-called training scenarios. Furthermore, a rich set of mathematical measures arises from the hybrid models such as triad census, dyad census, eigenvalues, utilization, feedback loops, etc., which provides a strong foundation for studying an emergency management organization. Future research will be necessary for analyzing real data and validating the proposed methodology.

With the advances in the information and computing technologies, the ways the manufacturing enterprise systems are being managed are changing. More integration and adoption of the system perspective push further towards a more flattened enterprise. This, in addition to the varying levels of aggregation and details and the presence of the continuous and discrete types of behavior, created serious challenges for the use of the existing simulation tools for simulating the modern manufacturing enterprise system. The commonly used discrete event simulation (DES) techniques face difficulties in modeling such integrated systems due to increased model complexity, the lack of data at the aggregate management levels, and the unsuitability of DES to model the financial sectors of the enterprise. System dynamics (SD) has been effective in providing the needs of top management levels but unsuccessful in offering the needed granularity at the detailed operational levels of the manufacturing system. On the other hand the existing hybrid continuous-discrete tools are based on certain assumptions that do not fit the requirements of the common decision making situations in the business systems. This research has identified a need for new simulation modeling approaches that responds to the changing business environments towards more integration and flattened enterprise systems. These tools should be able to develop comprehensive models that are inexpensive, scalable, and able to accommodate the continuous and discrete modes of behavior, the stochastic and deterministic natures of the various business units, and the detail complexity and dynamic complexity perspectives in decision making. The research proposes and develops a framework to combine and synchronize the SD and DES simulation paradigms to simulate the manufacturing enterprise system. The new approach can respond to the identified requirements in simulating the modern manufacturing enterprise systems. It is directed toward building comprehensive simulation models that can accommodate all management levels while explicitly recognizing the differences between them in terms of scope and frequency of decision making as well as the levels of details preferred and used at each level. This SDDES framework maintains the integrity of the two simulation paradigms and can use existing/legacy simulation models without requiring learning new simulation or computer programming skills. The new framework uses a modular structure by which the SD and DES models are treated as members of a comprehensive simulation. A new synchronization mechanism that that maintains the integrity of the two simulation paradigms and is not event-driven is utilized to coordinate the interactions between the simulation modules. It avoids having one simulation paradigm dominating the other. For communication and model management purposes the SDDES formalism provides a generic format to describe, specify, and document the simulation modules and the information sharing processes. The SDDES controller which is the communication manager, implements the synchronization mechanism and manages the simulation run ensuring correct exchange of data in terms of timeliness and format, between the modules. It also offers the user interface through which users interact with the simulation modules.

No description available.

Possibilities of generating plasma turbulence to provide control of space weather processes have been of particular interest in recent years. Such turbulence can be created by chemical released into a magnetized background plasma. The released plasma clouds are heavy ions which have ring velocity distribution and large free energy to drive the turbulence. An electromagnetic hybrid (fluid electrons and particle ions) model incorporating electron inertia is developed to study the generation and nonlinear evolution of this turbulence. Fourier pseudo-spectral methods are combined with finite difference methods to solve the electron momentum equations. Time integration is accomplished by a 4th-order Runge-Kutta scheme or predicator-corrector method. The numerical results show good agreement with theoretical prediction as well as provide further insights on the nonlinear turbulence evolution. Initially the turbulence lies near harmonics of the ring plasma ion cyclotron frequency and propagates nearly perpendicular to the background magnetic field as predicted by the linear theory. If the amplitude of the turbulence is sufficiently large, the quasi-electrostatic short wavelength ion cyclotron waves evolve nonlinearly into electromagnetic obliquely propagating shear Alfven waves with much longer wavelength. The results indicate that ring densities above a few percent of the background plasma density may produce wave amplitudes large enough for such an evolution to occur. The extraction of energy from the ring plasma may be in the range of 10-15% with a generally slight decrease in the magnitude as the ring density is increased from a few percent to several 10's of percent of the background plasma density. Possibilities to model the effects of nonlinear processes on energy extraction by introducing electron anomalous resistivity are also addressed. Suitability of the nonlinearly generated shear Alfven waves for applications to scattering radiation belt particles is discussed. / Master of Science

abstract: Two significant trends of recent power system evolution are: (1) increasing installa-tion of dynamic loads and distributed generation resources in distribution systems; (2) large-scale renewable energy integration at the transmission system level. A majority of these devices interface with power systems through power electronic converters. However, existing transient stability (TS) simulators are inadequate to represent the dynamic behavior of these devices accurately. On the other hand, simulating a large system using an electromagnetic transient (EMT) simulator is computationally impractical. EMT-TS hybrid simulation approach is an alternative to address these challenges. Furthermore, to thoroughly analyze the increased interactions among the transmission and distribution systems, an integrated modeling and simulation approach is essential. The thesis is divided into three parts. The first part focuses on an improved hybrid simulation approach and software development. Compared to the previous work, the pro-posed approach has three salient features: three-sequence TS simulation algorithm, three-phase/three-sequence network equivalencing and flexible switching of the serial and par-allel interaction protocols. The second part of the thesis concentrates on the applications of the hybrid simula-tion tool. The developed platform is first applied to conduct a detailed fault-induced de-layed voltage recovery (FIDVR) study on the Western Electricity Coordinating Council (WECC) system. This study uncovers that after a normally cleared single line to ground fault at the transmission system could cause air conditioner motors to stall in the distribu-tion systems, and the motor stalling could further propagate to an unfaulted phase under certain conditions. The developed tool is also applied to simulate power systems inter-faced with HVDC systems, including classical HVDC and the new generation voltage source converter (VSC)-HVDC system. The third part centers on the development of integrated transmission and distribution system simulation and an advanced hybrid simulation algorithm with a capability of switching from hybrid simulation mode to TS simulation. Firstly, a modeling framework suitable for integrated transmission and distribution systems is proposed. Secondly, a power flow algorithm and a diakoptics based dynamic simulation algorithm for the integrated transmission and distribution system are developed. Lastly, the EMT-TS hybrid simulation algorithm is combined with the diakoptics based dynamic simulation algorithm to realize flexible simulation mode switching to increase the simulation efficiency. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2016

Dans le domaine des systèmes distribués et du calcul haute performance, la validation expérimentale est de plus en plus utilisée par rapport aux approches analytiques. En effet, celles-ci sont de moins en moins réalisables à cause de la complexité grandissante de ces systèmes à la fois au niveau logiciel et matériel. Les chercheurs doivent donc faire face à de nombreux challenges lors de la réalisation de leurs expériences rendant le processus coûteux en ressource et en temps. Bien que de larges plateformes parallèles et technologies de virtualisation existent, les expérimentations sont, pour la plupart du temps, limitées en taille. La difficulté de passer une expérimentation à l'échelle représente un des grands facteurs limitant. Le niveau technique nécessaire pour mettre en place un environnement expérimentale approprié ne cesse d'augmenter pour suivre les évolutions des outils logiciels et matériels de plus en plus complexes. Par conséquent, les chercheurs sont tentés d'utiliser des méthodes ad-hoc pour présenter des résultats plus rapidement et pouvoir publier. Il devient alors difficile d'obtenir des informations sur ces expérimentations et encore plus de les reproduire.Une palette d'outils ont été proposés pour traiter cette complexité lors des expérimentations. Ces outils sont motivés par le besoin de fournir et d'encourager des méthodes expérimentales plus construites. Cependant, ces outils se concentrent principalement sur des scénarios très simple n'utilisant par exemple qu'un seul noeud ou client/serveur. Dans le contexte des systèmes distribués et du calcul haute performance, l'objectif de cette thèse est de faciliter la création d'expériences, de leur contrôle, répétition et archivage.Dans cette thèse nous proposons deux outils pour mener des expérimentations nécessitant une pile logicielle complexe ainsi qu'un grand nombre de ressources matérielles. Le premier outil est Expo. Il permet de contrôler efficacement la partie dynamique d'une expérimentation, c'est à dire l'enchaînement des tests expérimentaux, la surveillance des taches et la collecte des résultats. Expo dispose d'un langage de description qui permet de mettre en place une expérience dans un contexte distribué avec nettement moins de difficultés. Contrairement aux autres approches, des tests de passage à l'échelle et scénarios d'usage sont présentés afin de démontrer les avantages de notre approche. Le second outil est appelé Kameleon. Il traite les aspects statiques d'une expérience, c'est à dire la pile logicielle et sa configuration. Kameleon est un logiciel qui permet de décrire et contrôler toutes les étapes de construction d'un environnement logiciel destiné aux expérimentations. La principale contribution de Kamelon est de faciliter la construction d'environnements logiciels complexes ainsi que de garantir de futur reconstructions. / In the field of Distributed Systems and High Performance Computing experimental validation is heavily used against an analytic approach which is not feasible any more due to the complexity of those systems in terms of software and hardware.Therefore, researchers have to face many challenges when conducting their experiments, making the process costly and time consuming. Although world scale platforms exist and virtualization technologies enable to multiplex hardware, experiments are most of the time limited in size given the difficulty to perform them at large scale.The level of technical skills required for setting up an appropriate experimental environment is risen with the always increasing complexity of software stacks and hardware nowadays. This in turn provokes that researchers in the pressure to publish and present their results use ad hoc methodologies.Hence, experiments are difficult to track and preserve, preventing future reproduction. A variety of tools have been proposed to address this complexity at experimenting. They were motivated by the need to provide and encourage a sounder experimental process, however, those tools primary addressed much simpler scenarios such as single machine or client/server. In the context of Distributed Systems and High Performance Computing, the objective of this thesis is to make complex experiments, easier to perform, to control, to repeat and to archive. In this thesis we propose two tools for conducting experiments that demand a complex software stack and large scale. The first tool is Expo that enable to efficiently control the dynamic part of an experiment which means all the experiment workflow, monitoring of tasks, and collection of results.Expo features a description language that makes the set up of an experiment withdistributed systems less painful. Comparison against other approaches, scalability tests anduse cases are shown in this thesis which demonstrate the advantage of our approach.The second tool is called Kamelon which addresses the static part of an experiment,meaning the software stack and its configuration.Kameleon is a software appliance builderthat enables to describe and control all the process ofconstruction of a software stack for experimentation.The main contribution of Kameleon is to make easy the setup of complex software stacks andguarantee its post reconstruction.