992 resultados para DIGITAL SIMULATION


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Volatile organic compounds are a common source of groundwater contamination that can be easily removed by air stripping in columns with random packing and using a counter-current flow between the phases. This work proposes a new methodology for the column design for any particular type of packing and contaminant avoiding the necessity of a pre-defined diameter used in the classical approach. It also renders unnecessary the employment of the graphical Eckert generalized correlation for pressure drop estimates. The hydraulic features are previously chosen as a project criterion and only afterwards the mass transfer phenomena are incorporated, in opposition to conventional approach. The design procedure was translated into a convenient algorithm using C++ as programming language. A column was built in order to test the models used either in the design or in the simulation of the column performance. The experiments were fulfilled using a solution of chloroform in distilled water. Another model was built to simulate the operational performance of the column, both in steady state and in transient conditions. It consists in a system of two partial non linear differential equations (distributed parameters). Nevertheless, when flows are steady, the system became linear, although there is not an evident solution in analytical terms. In steady state the resulting system of ODE can be solved, allowing for the calculation of the concentration profile in both phases inside the column. In transient state the system of PDE was numerically solved by finite differences, after a previous linearization.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Informática

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Proceedings of IEEE, ISCAS 2003, Vol.I, pp. 877-880

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Dissertação submetida à Escola Superior de Teatro e Cinema para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Teatro - especialização em Encenação.

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This paper presents a model for the simulation of an offshore wind system having a rectifier input voltage malfunction at one phase. The offshore wind system model comprises a variable-speed wind turbine supported on a floating platform, equipped with a permanent magnet synchronous generator using full-power four-level neutral point clamped converter. The link from the offshore floating platform to the onshore electrical grid is done through a light high voltage direct current submarine cable. The drive train is modeled by a three-mass model. Considerations about the smart grid context are offered for the use of the model in such a context. The rectifier voltage malfunction domino effect is presented as a case study to show capabilities of the model. (C) 2015 Elsevier Ltd. All rights reserved.

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The iterative simulation of the Brownian bridge is well known. In this article, we present a vectorial simulation alternative based on Gaussian processes for machine learning regression that is suitable for interpreted programming languages implementations. We extend the vectorial simulation of path-dependent trajectories to other Gaussian processes, namely, sequences of Brownian bridges, geometric Brownian motion, fractional Brownian motion, and Ornstein-Ulenbeck mean reversion process.

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This work reports a theoretical study aimed to identify the plasmonic resonance condition for a system formed by metallic nanoparticles embedded in an a-Si: H matrix. The study is based on a Tauc-Lorentz model for the electrical permittivity of a-Si: H and a Drude model for the metallic nanoparticles. It is calculated the The polarizability of an sphere and ellipsoidal shaped metal nanoparticles with radius of 20 nm. We also performed FDTD simulations of light propagation inside this structure reporting a comparison among the effects caused by a single nanoparticles of Aluminium, Silver and, as a comparison, an ideally perfectly conductor. The simulation results shows that is possible to obtain a plasmonic resonance in the red part of the spectrum (600-700 nm) when 20-30 nm radius Aluminium ellipsoids are embedded into a-Si: H.

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This paper discusses the changes brought by the communication revolution in teaching and learning in the scope of LSP. Its aim is to provide an insight on how teaching which was bi-dimensional, turned into a multidimensional system, gathering other complementary resources that have transformed, in a incredibly short time, the ways we receive share and store information, for instance as professionals, and keep in touch with our peers. The increasing rise of electronic publications, the incredible boom of social and professional networks, search engines, blogs, list servs, forums, e-mail blasts, Facebook pages, YouTube contents, Tweets and Apps, have twisted the way information is conveyed. Classes ceased to be predictable and have been empowered by digital platforms, innumerous and different data repositories (TILDE, IATE, LINGUEE, and so many other terminological data banks) that have definitely transformed the academic world in general and tertiary education in particular. There is a bulk of information to be digested by students, who are no longer passive but instead responsible and active for their academic outcomes. The question is whether they possess the tools to select only what is accurate and important for a certain subject or assignment, due to that overflow? Due to the reduction of the number of course years in most degrees, after the implementation of Bologna and the shrinking of the curricula contents, have students the possibility of developing critical thinking? Both teaching and learning rely on digital resources to improve the speed of the spreading of knowledge. But have those changes been effective to promote really communication? Furthermore, with the increasing Apps that have already been developed and will continue to appear for learning foreign languages, for translation among others, will the students feel the need of learning them once they have those Apps. These are some the questions we would like to discuss in our paper.

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In today’s globalized world, communication students need to be capable of efficiently communicating across the globe. At ISCAP, part of the 3rd year syllabus in Translation and New Technologies course is focused on culture and the need to be culturally knowledgeable. We argue the approach to incorporate cultural aspects in HE needs to be studentcentered, in order to encompass not only intercultural awareness, but also the 21st century skills students need to be successful and competent citizens. Additionally, as studies have shown, the manipulation of digital tools fosters greater student involvement in learning activities. We have adopted Digital Storytelling - multimodal storytelling technique - to promote a personal, student-centered reflection on intercultural communication. We intend to present student and teacher perspectives on this learning experience and assess its relevance in HE contexts, based on the content analysis of student expressed perspectives on this activity as well as a multimodal analysis of the digital stories created. A preliminary analysis of our case study has demonstrated that Digital Storytelling potentiates two complimentary types of reflection: on the one hand, students felt the need to reflect on their own intercultural knowledge, create and adapt their finding in the form of a story; on the other hand, viewing others’ stories they have raised questions and demonstrated points of view otherwise ignored.

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A distributed, agent-based intelligent system models and simulates a smart grid using physical players and computationally simulated agents. The proposed system can assess the impact of demand response programs.

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Demand response can play a very relevant role in the context of power systems with an intensive use of distributed energy resources, from which renewable intermittent sources are a significant part. More active consumers participation can help improving the system reliability and decrease or defer the required investments. Demand response adequate use and management is even more important in competitive electricity markets. However, experience shows difficulties to make demand response be adequately used in this context, showing the need of research work in this area. The most important difficulties seem to be caused by inadequate business models and by inadequate demand response programs management. This paper contributes to developing methodologies and a computational infrastructure able to provide the involved players with adequate decision support on demand response programs and contracts design and use. The presented work uses DemSi, a demand response simulator that has been developed by the authors to simulate demand response actions and programs, which includes realistic power system simulation. It includes an optimization module for the application of demand response programs and contracts using deterministic and metaheuristic approaches. The proposed methodology is an important improvement in the simulator while providing adequate tools for demand response programs adoption by the involved players. A machine learning method based on clustering and classification techniques, resulting in a rule base concerning DR programs and contracts use, is also used. A case study concerning the use of demand response in an incident situation is presented.

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Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.

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Dissertação submetida à Escola Superior de Teatro e Cinema para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Desenvolvimento de projecto cinematográfico - Tecnologias de Pós-Produção