Modelação do transporte e dispersão atmosférica de poluentes produzidos por uma refinaria: estudo de caso

Mestrado em Engenharia Química.Ramo Tecnologias de Protecção Ambiental

Adaptive learning in agents behaviour: a framework for electricity markets simulation

Electricity markets are complex environments with very particular characteristics. A critical issue regarding these specific characteristics concerns the constant changes they are subject to. This is a result of the electricity markets’ restructuring, which was performed so that the competitiveness could be increased, but it also had exponential implications in the increase of the complexity and unpredictability in those markets scope. The constant growth in markets unpredictability resulted in an amplified need for market intervenient entities in foreseeing market behaviour. The need for understanding the market mechanisms and how the involved players’ interaction affects the outcomes of the markets, contributed to the growth of usage of simulation tools. Multi-agent based software is particularly well fitted to analyze dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This dissertation presents ALBidS – Adaptive Learning strategic Bidding System, a multiagent system created to provide decision support to market negotiating players. This system is integrated with the MASCEM electricity market simulator, so that its advantage in supporting a market player can be tested using cases based on real markets’ data. ALBidS considers several different methodologies based on very distinct approaches, to provide alternative suggestions of which are the best actions for the supported player to perform. The approach chosen as the players’ actual action is selected by the employment of reinforcement learning algorithms, which for each different situation, simulation circumstances and context, decides which proposed action is the one with higher possibility of achieving the most success. Some of the considered approaches are supported by a mechanism that creates profiles of competitor players. These profiles are built accordingly to their observed past actions and reactions when faced with specific situations, such as success and failure. The system’s context awareness and simulation circumstances analysis, both in terms of results performance and execution time adaptation, are complementary mechanisms, which endow ALBidS with further adaptation and learning capabilities.

Ampliação do reservatório de Custóias

O presente relatório é a última etapa para a obtenção do Grau de Mestre em Tecnologia e Gestão das Construções leccionado no Instituto Superior de Engenharia do Porto, (ISEP). O estágio decorreu em ambiente maioritariamente de obra na empresa Monte Adriano, Engenharia e Construção, SA, e o objectivo consistiu em dar apoio e acompanhar a Obra de Ampliação do Reservatório de Custóias, inserida na Empreita de concepção, projecto e construção das infraestruturas necessárias à execução do plano de investimentos da Indáqua Matosinhos, actividades estas, decorrentes da função de adjunta de direcção de obra. Para além da breve descrição da empresa que a estagiária integrou e da empreitada geral, foi feita uma enumeração das várias actividades desempenhadas na Obra e dos vários condicionalismos encontrados que por vezes levaram a alterações do projecto. Dá-se especial ênfase à parte da execução das fundações, quer pela heterogeneidade do solo e sua relevância no geral, quer pelo facto do tempo de execução da obra ser praticamente o tempo do estágio. A obra consiste na execução de três células em painéis pré-fabricados SOPLACAS (paredes e cobertura), sendo que, as lajes de soleira de duas das células apoiam em poços e a laje de soleira da outra célula apoia directamente no terreno e em poços. Anexa às células encontra-se a câmara de manobras, executada em estrutura de betão armado.

Planeamento de curto prazo de sistemas de energia solar usando técnicas de otimização robusta

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica

Sistema de reconhecimento de impressões digitais baseado em FPGA

Trabalho de Projeto para obtenção do grau de Mestre em Engenharia de Eletrónica e Telecomunicações

On the adaptation of broadcast transactions in token-passing fieldbus networks with heterogeneous transmission media

Broadcast networks that are characterised by having different physical layers (PhL) demand some kind of traffic adaptation between segments, in order to avoid traffic congestion in linking devices. In many LANs, this problem is solved by the actual linking devices, which use some kind of flow control mechanism that either tell transmitting stations to pause (the transmission) or just discard frames. In this paper, we address the case of token-passing fieldbus networks operating in a broadcast fashion and involving message transactions over heterogeneous (wired or wireless) physical layers. For the addressed case, real-time and reliability requirements demand a different solution to the traffic adaptation problem. Our approach relies on the insertion of an appropriate idle time before a station issuing a request frame. In this way, we guarantee that the linking devices’ queues do not increase in a way that the timeliness properties of the overall system turn out to be unsuitable for the targeted applications.

Timing analysis of an inter-cell mobility procedure for a wired/wireless PROFIBUS network

Recently, there have been a few research efforts towards extending the capabilities of fieldbus networks to encompass wireless support. In previous works we have proposed a hybrid wired/wireless PROFIBUS network solution where the interconnection between the heterogeneous communication media was accomplished through bridge-like interconnecting devices. The resulting networking architecture embraced a Multiple Logical Ring (MLR) approach, thus with multiple independent tokens, where the communication between different domains was supported by the Inter-Domain Protocol (IDP). The proposed architecture also supports mobility of stations between different wireless cells. To that hybrid wired/wireless networking architecture we have proposed a worst-case response timing analysis of the IDP, without considering inter-cell mobility (or handoff) of stations. In this paper, we advance that previous work by proposing a worst-case timing analysis of the mobility procedure.

Timing analysis of a multiple logical ring wired/wireless PROFIBUS network

Recently, there have been a few research efforts towards extending the capabilities of fieldbus networks to encompass wireless support. In previous works we have proposed a hybrid wired/wireless PROFIBUS network solution where the interconnection between the heterogeneous communication media was accomplished through bridge-like interconnecting devices. The resulting networking architecture embraced a multiple logical ring (MLR) approach, thus with multiple independent tokens, to which a specific bridging protocol extension, the inter-domain protocol (IDP), was proposed. The IDP offers compatibility with standard PROFIBUS, and includes mechanisms to support inter-cell mobility of wireless nodes. We advance that work by proposing a worst-case response timing analysis of the IDP.

An improved preemption delay upper bound for floating non-preemptive region

In embedded systems, the timing behaviour of the control mechanisms are sometimes of critical importance for the operational safety. These high criticality systems require strict compliance with the offline predicted task execution time. The execution of a task when subject to preemption may vary significantly in comparison to its non-preemptive execution. Hence, when preemptive scheduling is required to operate the workload, preemption delay estimation is of paramount importance. In this paper a preemption delay estimation method for floating non-preemptive scheduling policies is presented. This work builds on [1], extending the model and optimising it considerably. The preemption delay function is subject to a major tightness improvement, considering the WCET analysis context. Moreover more information is provided as well in the form of an extrinsic cache misses function, which enables the method to provide a solution in situations where the non-preemptive regions sizes are small. Finally experimental results from the implementation of the proposed solutions in Heptane are provided for real benchmarks which validate the significance of this work.

Intra-type migrative scheduling of implicit-deadline sporadic tasks on two- type heterogeneous multiprocessor

Consider the problem of scheduling a set of implicit-deadline sporadic tasks to meet all deadlines on a two-type heterogeneous multiprocessor platform. Each processor is either of type-1 or type-2 with each task having different execution time on each processor type. Jobs can migrate between processors of same type (referred to as intra-type migration) but cannot migrate between processors of different types. We present a new scheduling algorithm namely, LP-Relax(THR) which offers a guarantee that if a task set can be scheduled to meet deadlines by an optimal task assignment scheme that allows intra-type migration then LP-Relax(THR) meets deadlines as well with intra-type migration if given processors 1/THR as fast (referred to as speed competitive ratio) where THR <= 2/3.

On the capacity of cluster-tree ZigBee networks

Modeling the fundamental performance limits of Wireless Sensor Networks (WSNs) is of paramount importance to understand their behavior under worst-case conditions and to make the appropriate design choices. In that direction this paper contributes with an analytical methodology for modeling cluster-tree WSNs where the data sink can either be static or mobile. We assess the validity and pessimism of analytical model by comparing the worst-case results with the values measured through an experimental test-bed based on Commercial-Off- The-Shelf (COTS) technologies, namely TelosB motes running TinyOS.

Partial utility-driven scheduling for flexible SLA and pricing arbitration in clouds

Cloud SLAs compensate customers with credits when average availability drops below certain levels. This is too inflexible because consumers lose non-measurable amounts of performance being only compensated later, in next charging cycles. We propose to schedule virtual machines (VMs), driven by range-based non-linear reductions of utility, different for classes of users and across different ranges of resource allocations: partial utility. This customer-defined metric, allows providers transferring resources between VMs in meaningful and economically efficient ways. We define a comprehensive cost model incorporating partial utility given by clients to a certain level of degradation, when VMs are allocated in overcommitted environments (Public, Private, Community Clouds). CloudSim was extended to support our scheduling model. Several simulation scenarios with synthetic and real workloads are presented, using datacenters with different dimensions regarding the number of servers and computational capacity. We show the partial utility-driven driven scheduling allows more VMs to be allocated. It brings benefits to providers, regarding revenue and resource utilization, allowing for more revenue per resource allocated and scaling well with the size of datacenters when comparing with an utility-oblivious redistribution of resources. Regarding clients, their workloads’ execution time is also improved, by incorporating an SLA-based redistribution of their VM’s computational power.

A type system for access control in an object-oriented language

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

Deterministic approach for multiple-source tsunami hazard assessment for Sines, Portugal

In this paper, we present a deterministic approach to tsunami hazard assessment for the city and harbour of Sines, Portugal, one of the test sites of project ASTARTE (Assessment, STrategy And Risk Reduction for Tsunamis in Europe). Sines has one of the most important deep-water ports, which has oil-bearing, petrochemical, liquid-bulk, coal, and container terminals. The port and its industrial infrastructures face the ocean southwest towards the main seismogenic sources. This work considers two different seismic zones: the Southwest Iberian Margin and the Gloria Fault. Within these two regions, we selected a total of six scenarios to assess the tsunami impact at the test site. The tsunami simulations are computed using NSWING, a Non-linear Shallow Water model wIth Nested Grids. In this study, the static effect of tides is analysed for three different tidal stages: MLLW (mean lower low water), MSL (mean sea level), and MHHW (mean higher high water). For each scenario, the tsunami hazard is described by maximum values of wave height, flow depth, drawback, maximum inundation area and run-up. Synthetic waveforms are computed at virtual tide gauges at specific locations outside and inside the harbour. The final results describe the impact at the Sines test site considering the single scenarios at mean sea level, the aggregate scenario, and the influence of the tide on the aggregate scenario. The results confirm the composite source of Horseshoe and Marques de Pombal faults as the worst-case scenario, with wave heights of over 10 m, which reach the coast approximately 22 min after the rupture. It dominates the aggregate scenario by about 60 % of the impact area at the test site, considering maximum wave height and maximum flow depth. The HSMPF scenario inundates a total area of 3.5 km2. © Author(s) 2015.

Solar Intensity Forecasting using Artificial Neural Networks and Support Vector Machines

This paper presents several forecasting methodologies based on the application of Artificial Neural Networks (ANN) and Support Vector Machines (SVM), directed to the prediction of the solar radiance intensity. The methodologies differ from each other by using different information in the training of the methods, i.e, different environmental complementary fields such as the wind speed, temperature, and humidity. Additionally, different ways of considering the data series information have been considered. Sensitivity testing has been performed on all methodologies in order to achieve the best parameterizations for the proposed approaches. Results show that the SVM approach using the exponential Radial Basis Function (eRBF) is capable of achieving the best forecasting results, and in half execution time of the ANN based approaches.