52 resultados para Transport Modelling


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Digital Businesses have become a major driver for economic growth and have seen an explosion of new startups. At the same time, it also includes mature enterprises that have become global giants in a relatively short period of time. Digital Businesses have unique characteristics that make the running and management of a Digital Business much different from traditional offline businesses. Digital businesses respond to online users who are highly interconnected and networked. This enables a rapid flow of word of mouth, at a pace far greater than ever envisioned when dealing with traditional products and services. The relatively low cost of incremental user addition has led to a variety of innovation in pricing of digital products, including various forms of free and freemium pricing models. This thesis explores the unique characteristics and complexities of Digital Businesses and its implications on the design of Digital Business Models and Revenue Models. The thesis proposes an Agent Based Modeling Framework that can be used to develop Simulation Models that simulate the complex dynamics of Digital Businesses and the user interactions between users of a digital product. Such Simulation models can be used for a variety of purposes such as simple forecasting, analysing the impact of market disturbances, analysing the impact of changes in pricing models and optimising the pricing for maximum revenue generation or a balance between growth in usage and revenue generation. These models can be developed for a mature enterprise with a large historical record of user growth rate as well as for early stage enterprises without much historical data. Through three case studies, the thesis demonstrates the applicability of the Framework and its potential applications.

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This thesis is a study of how heat is transported in non-steady-state conditions from a superconducting Rutherford cable to a bath of superfluid helium (He II). The same type of superconducting cable is used in the dipole magnets of the Large Hadron Collider (LHC). The dipole magnets of the LHC are immersed in a bath of He II at 1.9 K. At this temperature helium has an extremely high thermal conductivity. During operation, heat needs to be efficiently extracted from the dipole magnets to keep their superconducting state. The thermal stability of the magnets is crucial for the operation of the LHC, therefore it is necessary to understand how heat is transported from the superconducting cables to the He II bath. In He II the heat transfer can be described by the Landau regime or by the Gorter-Mellink regime, depending on the heat flux. In this thesis both measurements and numerical simulation have been performed to study the heat transfer in the two regimes. A temperature increase of 8 2 mK of the superconducting cables was successfully measured experimentally. A new numerical model that covers the two heat transfer regimes has been developed. The numerical model has been validated by comparison with existing experimental data. A comparison is made between the measurements and the numerical results obtained with the developed model.

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With the projection of an increasing world population, hand-in-hand with a journey towards a bigger number of developed countries, further demand on basic chemical building blocks, as ethylene and propylene, has to be properly addressed in the next decades. The methanol-to-olefins (MTO) is an interesting reaction to produce those alkenes using coal, gas or alternative sources, like biomass, through syngas as a source for the production of methanol. This technology has been widely applied since 1985 and most of the processes are making use of zeolites as catalysts, particularly ZSM-5. Although its selectivity is not especially biased over light olefins, it resists to a quick deactivation by coke deposition, making it quite attractive when it comes to industrial environments; nevertheless, this is a highly exothermic reaction, which is hard to control and to anticipate problems, such as temperature runaways or hot-spots, inside the catalytic bed. The main focus of this project is to study those temperature effects, by addressing both experimental, where the catalytic performance and the temperature profiles are studied, and modelling fronts, which consists in a five step strategy to predict the weight fractions and activity. The mind-set of catalytic testing is present in all the developed assays. It was verified that the selectivity towards light olefins increases with temperature, although this also leads to a much faster catalyst deactivation. To oppose this effect, experiments were carried using a diluted bed, having been able to increase the catalyst lifetime between 32% and 47%. Additionally, experiments with three thermocouples placed inside the catalytic bed were performed, analysing the deactivation wave and the peaks of temperature throughout the bed. Regeneration was done between consecutive runs and it was concluded that this action can be a powerful means to increase the catalyst lifetime, maintaining a constant selectivity towards light olefins, by losing acid strength in a steam stabilised zeolitic structure. On the other hand, developments on the other approach lead to the construction of a raw basic model, able to predict weight fractions, that should be tuned to be a tool for deactivation and temperature profiles prediction.

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Combinatorial Optimization Problems occur in a wide variety of contexts and generally are NP-hard problems. At a corporate level solving this problems is of great importance since they contribute to the optimization of operational costs. In this thesis we propose to solve the Public Transport Bus Assignment problem considering an heterogeneous fleet and line exchanges, a variant of the Multi-Depot Vehicle Scheduling Problem in which additional constraints are enforced to model a real life scenario. The number of constraints involved and the large number of variables makes impracticable solving to optimality using complete search techniques. Therefore, we explore metaheuristics, that sacrifice optimality to produce solutions in feasible time. More concretely, we focus on the development of algorithms based on a sophisticated metaheuristic, Ant-Colony Optimization (ACO), which is based on a stochastic learning mechanism. For complex problems with a considerable number of constraints, sophisticated metaheuristics may fail to produce quality solutions in a reasonable amount of time. Thus, we developed parallel shared-memory (SM) synchronous ACO algorithms, however, synchronism originates the straggler problem. Therefore, we proposed three SM asynchronous algorithms that break the original algorithm semantics and differ on the degree of concurrency allowed while manipulating the learned information. Our results show that our sequential ACO algorithms produced better solutions than a Restarts metaheuristic, the ACO algorithms were able to learn and better solutions were achieved by increasing the amount of cooperation (number of search agents). Regarding parallel algorithms, our asynchronous ACO algorithms outperformed synchronous ones in terms of speedup and solution quality, achieving speedups of 17.6x. The cooperation scheme imposed by asynchronism also achieved a better learning rate than the original one.

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This paper aims to provide a model that allows BPI to measure the credit risk, through its rating scale, of the subsidiaries included in the corporate groups who are their clients. This model should be simple enough to be applied in practice, accurate, and must give consistent results in comparison to what have been the ratings given by the bank. The model proposed includes operational, strategic, and financial factors and ends up giving one of three results: no support, partial support, or full support from the holding to the subsidiary, and each of them translates in adjustments in each subsidiary’s credit rating. As it would be expectable, most of the subsidiaries should have the same credit rating of its parent company.

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The thrust towards energy conservation and reduced environmental footprint has fueled intensive research for alternative low cost sources of renewable energy. Organic photovoltaic cells (OPVs), with their low fabrication costs, easy processing and flexibility, represent a possible viable alternative. Perylene diimides (PDIs) are promising electron-acceptor candidates for bulk heterojunction (BHJ) OPVs, as they combine higher absorption and stability with tunable material properties, such as solubility and position of the lowest unoccupied molecular orbital (LUMO) level. A prerequisite for trap free electron transport is for the LUMO to be located at a level deeper than 3.7 eV since electron trapping in organic semiconductors is universal and dominated by a trap level located at 3.6 eV. Although the mostly used fullerene acceptors in polymer:fullerene solar cells feature trap-free electron transport, low optical absorption of fullerene derivatives limits maximum attainable efficiency. In this thesis, we try to get a better understanding of the electronic properties of PDIs, with a focus on charge carrier transport characteristics and the effect of different processing conditions such as annealing temperature and top contact (cathode) material. We report on a commercially available PDI and three PDI derivatives as acceptor materials, and its blends with MEH-PPV (Poly[2-methoxy 5-(2-ethylhexyloxy)-1,4-phenylenevinylene]) and P3HT (Poly(3-hexylthiophene-2,5-diyl)) donor materials in single carrier devices (electron-only and hole-only) and in solar cells. Space-charge limited current measurements and modelling of temperature dependent J-V characteristics confirmed that the electron transport is essentially trap-free in such materials. Different blend ratios of P3HT:PDI-1 (1:1) and (1:3) show increase in the device performance with increasing PDI-1 ratio. Furthermore, thermal annealing of the devices have a significant effect in the solar cells that decreases open-circuit voltage (Voc) and fill factor FF, but increases short-circuit current (Jsc) and overall device performance. Morphological studies show that over-aggregation in traditional donor:PDI blend systems is still a big problem, which hinders charge carrier transport and performance in solar cells.