O fenômeno do congestionamento, decorrente do rápido aumento da demanda por todos os meios de transporte só tende a se agravar, já que sistemas de transporte (vistos como um todo) têm um grande impacto na economia mundial. No caso do transporte veicular em particular, é notório que a demanda por mobilidade é uma das características da nossa sociedade. O impacto direto e indireto dos congestionamentos em áreas urbanas e interurbanas é imenso, e precisam ser avaliados adequadamente para que seus efeitos sejam pelo menos minorados. Esta dissertação apresenta o AVNET, uma modelagem baseada em agentes para avali- ação do balanceamento de carga em redes de tráfego veicular, capaz de investigar micros- copicamente a interação entre oferta, demanda e as particularidades do comportamento dos motoristas, aqui tratados como agentes autônomos capazes de perceber o estado do ambiente e se adaptar a ele utilizando replanejamento heurístico. O principal objetivo do AVNET é investigar a interação entre a percepção que o agente possui do tráfego e a consequente adaptação através da mudança de rota durante a viagem. De forma cíclica, o AVNET propõe que o estado do ambiente influencia na percepção do agente, e a ação do agente influencia no estado do ambiente. As medidas de balanceamento de carga visam avaliar o desempenho do ponto de vista do motorista, ao invés de abordar a avaliação do ponto de vista da rede como algumas abordagens tradicionalmente propõe. Experimentos foram realizados a partir da variação nas condições de oferta - utili- zando uma rede com topologia em estilo de grade e uma abstração de algumas vias arte- riais da cidade de Porto Alegre/RS - variação nas condições de demanda - o tipo de dis- tribuição e número de viagens - e dos tipos de agentes utilizados. Os resultados ajudam a responder como será o balanceamento de carga de redes de tráfego veicular conforme as condições de oferta e demanda do ambiente, e de percepção/ação dos agentes. / The phenomenon of congestion, due to the rapid increase in demand for all means of transport is only going to worsen, since systems transport (seen as a whole) have a major impact on the world economy. In the case of vehicular transport in particular, it is clear that the demand for mobility is a characteristic of our society. The direct and indirect impact of congestion in urban and long distance is immense, and must be properly evaluated for their effects are at least mitigated. This dissertation presents the AVNET, an agent-basead modelling to evaluate load bal- ancing in networks of vehicular traffic, able to microscopically investigate the interaction between supply, demand and the peculiarities of the behavior of drivers, here treated as autonomous agents, capable to perceive the state of the environment and adapt to it using heuristic redesign. The main goal of AVNET is to investigate the interaction between the perception that the agent has the traffic and the consequent adaptation by changing the route during the trip. Cyclically, the AVNET propose that the state of the environment influences the perception of the agent and the agent’s action influences the state of the environment. Experiments were performed from the variation in supply conditions - using a network grid topology and an abstraction of some arterial roads in the city of Porto Alegre/RS - changes in demand conditions - the type of distribution and number of trips - and the types of agents used. The results will help answer how the balancing network load of vehicular traffic as conditions of supply and demand of the environment, and perception / action agents.

Iron is essential for virtually all organisms, yet it can be highly toxic if not properly regulated. Only the Lyme disease pathogen Borrelia burgdorferi has evolved to not require iron (Aguirre et al., 2013).Recent findings have characterised elements of the iron metabolism network, but understanding of systemic iron regulation remains poor. To improve understanding and provide a tool for in silico experimentation, a computational model of human iron metabolism has been constructed. COPASI was utilised to construct a model that included detailed modelling of iron metabolism in liver and intestinal cells. Inter-cellular interactions and dietary iron absorption were included to create a systemic computational model. Parameterisation was performed using a wide variety of literature data. Validation of the model was performed using published experimental and clinical findings, and the model was found to recreate quantitatively and accurately many results. Analysis of sensitivities in the model showed that, despite enterocytes being the only route of iron uptake, almost all control over the system is provided by reactions in the liver. Metabolic control analysis identified key regulatory factors and potential therapeutic targets. A virtual haemochromatosis patient was created and compared to a simulation of a healthy human. The redistribution of control in haemochromatosis was analysed in order to improve our understanding of the condition and identify promising therapeutic targets. Cellular prion protein (PrP) is an enigmatic protein, implicated in disease when misfolded, but its physiological role remains a mystery. PrP was recently found to have ferric-reductase capacity. Potential sites of ferric reduction were simulated and the findings compared to PrP knockout mice experiments. I propose that the physiological role of PrP is in the chemical reduction of endocytosed ferric iron to its ferrous form following transferrin receptor-mediated uptake.

This thesis, within a long-term project at the Institute of automotive engineering at FME BUT, aspires to prepare a motorcycle for analysis of its dynamic riding behavior. A multi-body model of a motorcycle is created based on the measured parameters and a system for measuring driving conditions is designed. The necessary motorcycle parameters were measured using a 3D scanner and through experiments aided by computer technology and CAD software. This laid the foundation for the follow-up research and development work.

This dissertation addresses the challenges of scoping and sizing components and modeling the tank to wheel energy flows in new and rapidly evolving classes of automotive vehicles. It introduces a system of computer models, known as the Oxford Vehicle Model (OVEM), which provide for the novel simulation of the powertrains of electric (EV) and hybrid electric vehicles (HEV). OVEM has a three-level structure that makes a unique contribution to the field of vehicle analysis by enabling a user to proceed from performing scoping and sizing exercises through to accurately simulating the energy flows in powertrains of EVs and HEVs utilizing existing and emerging technologies based on real world data. Level 1 uses simplified models to support initial component scoping and sizing exercises in an analysis environment where uncertainty regarding component specifications is high. Level 2 builds on Level 1 by obtaining more refined component scoping and sizing estimates via the use of component models based on well-understood scientific principles that are product-independent – a crucial feature for obtaining unbiased scoping and sizing estimates. Level 3 employs a high degree of fidelity in that its models impose actual physical limits and are based on data from real technologies. This dissertation concludes with two chapters based on studies published as journal articles that used OVEM to address key issues facing the development of EVs and HEVs. The first study used OVEM to make the novel comparison between high-speed flywheels, batteries, and ultracapacitors on the bases of cost and fuel consumption while functioning as the energy storage systems in an HEV. The second study applied OVEM towards a novel examination of the CO2 emissions from plug-in HEVs (PHEVs) and compares their CO2 emissions to those from similar EVs and ICE-based vehicles.

There are many methods for modelling the reliability of systems based on component failure data. This task becomes more complex as systems increase in size, or undertake missions that comprise multiple discrete modes of operation, or phases. Existing techniques require certain levels of expertise in the model generation and calculation processes, meaning that risk and reliability assessments of systems can often be expensive and time-consuming. This is exacerbated as system complexity increases. This thesis presents a novel method which generates reliability models for phasedmission systems, based on Petri nets, from simple input files. The process has been automated with a piece of software designed for engineers with little or no experience in the field of risk and reliability. The software can generate models for both repairable and non-repairable systems, allowing redundant components and maintenance cycles to be included in the model. Further, the software includes a simulator for the generated models. This allows a user with simple input files to perform automatic model generation and simulation with a single piece of software, yielding detailed failure data on components, phases, missions and the overall system. A system can also be simulated across multiple consecutive missions. To assess performance, the software is compared with an analytical approach and found to match within 5% in both the repairable and non-repairable cases. The software documented in this thesis could serve as an aid to engineers designing new systems to validate the reliability of the system. This would not require specialist consultants or additional software, ensuring that the analysis provides results in a timely and cost-effective manner.

Micrometer injection moulding is a type of moulding in which moulds have geometrical design features on a micrometer scale that must be transferred to the geometry of the produced part. The difficulties encountered due to very high shear and rapid heat transfer of these systems has motivated this investigation into the fundamental mathematics behind polymer heat transfer and associated processes. The aim is to derive models for polymer dynamics, especially heat dynamics, that are considerably less approximate than the ones used at present, and to translate this into simulation and optimisation algorithms and strategies, Thereby allowing for greater control of the various polymer processing methods at micrometer scales.

<p>We review a number of compartmental models in epidemiology which leads to a nonlinear system of ordinary differential equations. We focus an SIR, SEIR and SIS epidemic models with and without vaccination. A threshold parameter R0 is identified which governs the spread of diseases, and this parameter is known as the basic reproductive number. The models have at least two equilibria, an endemic equilibrium and the disease-free equilibrium. We demonstrate that the disease will die out, if the basic reproductive number R0 &lt / 1. This is the case of a disease-free&nbsp / state, with no infection in the population. Otherwise the disease may become endemic if the basic reproductive number R0 is bigger than unity. Furthermore, stability analysis for both endemic&nbsp / and disease-free steady states are investigated and we also give some numerical simulations. The second part of this dissertation deals with optimal vaccination strategy in epidemiology. We&nbsp / use optimal control technique on vaccination to minimize the impact of the disease. Hereby we mean minimizing the spread of the disease in the population, while also minimizing the effort on&nbsp / vaccination roll-out. We do this optimization for the cases of SIR and SEIR models, and show how optimal strategies can be obtained which minimize the damage caused by the infectious&nbsp / disease. Finally, we describe the numerical simulations using the fourth-order Runge-Kutta method.&nbsp / These are the most useful references: [G. Zaman, Y.H Kang, II. H. Jung. BioSystems 93,&nbsp / (2008), 240 &minus / 249], [K. Hattaf, N. Yousfi. The Journal of Advanced Studies in Biology, Vol. 1(8), (2008), 383 &minus / 390.], [Lenhart, J.T. Workman. Optimal Control and Applied to Biological Models.&nbsp / Chapman and Hall/CRC, (2007).], [P. Van den Driessche, J. Watmough. Math. Biosci., 7,&nbsp / (2005)], and [J. Wu, G. R&uml / ost. Mathematical Biosciences and Engineering, Vol 5(2), (2008), 389 &minus / 391].</p>

<p>We review a number of compartmental models in epidemiology which leads to a nonlinear system of ordinary differential equations. We focus an SIR, SEIR and SIS epidemic models with and without vaccination. A threshold parameter R0 is identified which governs the spread of diseases, and this parameter is known as the basic reproductive number. The models have at least two equilibria, an endemic equilibrium and the disease-free equilibrium. We demonstrate that the disease will die out, if the basic reproductive number R0 &lt / 1. This is the case of a disease-free&nbsp / state, with no infection in the population. Otherwise the disease may become endemic if the basic reproductive number R0 is bigger than unity. Furthermore, stability analysis for both endemic&nbsp / and disease-free steady states are investigated and we also give some numerical simulations. The second part of this dissertation deals with optimal vaccination strategy in epidemiology. We&nbsp / use optimal control technique on vaccination to minimize the impact of the disease. Hereby we mean minimizing the spread of the disease in the population, while also minimizing the effort on&nbsp / vaccination roll-out. We do this optimization for the cases of SIR and SEIR models, and show how optimal strategies can be obtained which minimize the damage caused by the infectious&nbsp / disease. Finally, we describe the numerical simulations using the fourth-order Runge-Kutta method.&nbsp / These are the most useful references: [G. Zaman, Y.H Kang, II. H. Jung. BioSystems 93,&nbsp / (2008), 240 &minus / 249], [K. Hattaf, N. Yousfi. The Journal of Advanced Studies in Biology, Vol. 1(8), (2008), 383 &minus / 390.], [Lenhart, J.T. Workman. Optimal Control and Applied to Biological Models.&nbsp / Chapman and Hall/CRC, (2007).], [P. Van den Driessche, J. Watmough. Math. Biosci., 7,&nbsp / (2005)], and [J. Wu, G. R&uml / ost. Mathematical Biosciences and Engineering, Vol 5(2), (2008), 389 &minus / 391].</p>

Within the AutoDrive project, openPASS is used to develop a cognitive stochastic traffic flow simulation for urban intersections and highway scenarios, which are described in deliverable D1.14. The deliverable D2.16 includes the customizations of the framework openPASS that are required to provide a basis for the development and implementation of the driver behavior model and the evaluated safety function. The trial design for the evaluation of the safety functions is described. Furthermore, the design of the driver behavior study is introduced to parameterize and validate the underlying driver behavior model.

As part of the AutoDrive project, OpenPASS is used to develop a cognitive-stochastic traffic flow simulation for urban intersection scenarios described in deliverable D1.14. The deliverable D4.20 is about the design of the modules for the stochastic traffic simulation. This initially includes an examination of the existing traffic simulations described in chapter 2. Subsequently, the underlying tasks of the driver when crossing an intersection are explained. The main part contains the design of the cognitive structure of the road user (chapter 4.2) and the development of the cognitive behaviour modules (chapter 4.3).