Manutenção proactiva de sistemas AVAC com recurso aos sistemas inteligentes multiagente

Nos tempos actuais os equipamentos para Aquecimento Ventilação e Ar Condicionado (AVAC) ocupam um lugar de grande importância na concepção, desenvolvimento e manutenção de qualquer edifício por mais pequeno que este seja. Assim, surge a necessidade premente de racionalizar os consumos energéticos optimizando-os. A alta fiabilidade desejada nestes sistemas obriga-nos cada vez mais a descobrir formas de tornar a sua manutenção mais eficiente, pelo que é necessário prevenir de uma forma proactiva todas as falhas que possam prejudicar o bom desempenho destas instalações. Como tal, torna-se necessário detectar estas falhas/anomalias, sendo imprescíndivel que nos antecipemos a estes eventos prevendo o seu acontecimento num horizonte temporal pré-definido, permitindo actuar o mais cedo possível. É neste domínio que a presente dissertação tenta encontrar soluções para que a manutenção destes equipamentos aconteça de uma forma proactiva e o mais eficazmente possível. A ideia estruturante é a de tentar intervir ainda numa fase incipiente do problema, alterando o comportamento dos equipamentos monitorizados, de uma forma automática, com recursos a agentes inteligentes de diagnóstico de falhas. No caso em estudo tenta-se adaptar de forma automática o funcionamento de uma Unidade de Tratamento de Ar (UTA) aos desvios/anomalias detectadas, promovendo a paragem integral do sistema apenas como último recurso. A arquitectura aplicada baseia-se na utilização de técnicas de inteligência artificial, nomeadamente dos sistemas multiagente. O algoritmo utilizado e testado foi construído em Labview®, utilizando um kit de ferramentas de controlo inteligente para Labview®. O sistema proposto é validado através de um simulador com o qual se conseguem reproduzir as condições reais de funcionamento de uma UTA.

Gestão sustentável da água em empreendimentos turísticos

O presente documento enquadra-se no âmbito do trabalho final do mestrado (TFM) do curso de Engenharia Civil, na área de especialização de Hidráulica, do Instituto Superior de Engenharia de Lisboa, sob a forma de um projeto na fase de estudo prévio com o título ―Gestão Sustentável da Água no empreendimento turístico Parque de Campismo da Ilha do Pessegueiro situado em Porto Covo - Região de Turismo do Alentejo‖. Este trabalho é constituído essencialmente por 5 partes. Sendo a primeira uma breve introdução às questões a abordar, a segunda corresponde à discrição teórica do uso eficiente da água baseando-se no PNEUA (Programa nacional para o uso eficiente da água). Já a terceira parte é relativa ao atual sistema de utilização da água no Parque de campismo da ilha do pessegueiro (PCIP), sendo a quarta o estudo do desenvolvimento do projecto para a gestão eficiente da água no empreendimento e a quinta parte o estudo de viabilidade económica e financeira a implementar no projecto. Para além da implementação de medidas de poupança são também objetivos principais deste trabalho a reutilização da água através da recolha, o tratamento e armazenamento das águas residuais e aproveitamento das águas pluviais para posterior abastecimento do sistema de utilização em descargas sanitárias, lavagem de pavimentos e regas de espaços verdes. São, portanto, três os subsistemas de gestão eficiente da água que se pretende implementar. Dá-se importância ao estudo de viabilidade económica do projeto, cujo período de retorno do capital investido em capitais próprios e alheios é de seis anos. Este projeto pretende dar apoio técnico ao uso eficiente da água no PCIP, de forma a conseguir por um lado obter vantagens económicas e por outro proteger o ambiente. As vantagens económicas são interessantes para orientar os recursos financeiros para outros investimentos e as questões ambientais são a base de uma campanha, já em curso, para obtenção de certificação energética, em conjunto com outras práticas já em curso, nomeadamente a recolha seletiva de resíduos sólidos para recircular e aproveitamento de energia solar.

Implementação de um plano de segurança de águas num hospital

Dissertação de Natureza Científica para obtenção do grau de Mestre em Engenharia Civil

Estágio profissional em gabinete de engenharia, na componente de climatização

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica com Especialização em Energia, Climatização e Refrigeração

Optimizing the renewable generation mix in the Portuguese power system based on temporal and spatial diversity

Renewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.

Optimizing the renewable generation mix in the portuguese power system based on temporal and spatial diversity

Renewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.

Assessment and optimization of wind energy integration into the power systems: application to the portuguese system

The increasing integration of wind energy in power systems can be responsible for the occurrence of over-generation, especially during the off-peak periods. This paper presents a dedicated methodology to identify and quantify the occurrence of this over-generation and to evaluate some of the solutions that can be adopted to mitigate this problem. The methodology is applied to the Portuguese power system, in which the wind energy is expected to represent more than 25% of the installed capacity in a near future. The results show that the pumped-hydro units will not provide enough energy storage capacity and, therefore, wind curtailments are expected to occur in the Portuguese system. Additional energy storage devices can be implemented to offset the wind energy curtailments. However, the investment analysis performed show that they are not economically viable, due to the present high capital costs involved.

Comparison of body fat content and distribution of familial amyloidotic polyneuropathy patients versus healthy subjects

The deposition of amyloid fibers at the peripheral nervous system can induce motor neuropathy in Familial Amiloidotic Polyneuropethy (FAP) patients. This produces progressive reductions in functional capacity. The only treatment for FAP is a liver transplant, followed by aggressive medication that can affect patients' metabolism. To our knowledge, there are no data on body fat distribution or comparison between healthy and FAP subjects, which may be important for clinical assessment and management of this disease. PURPOSE: To analyze body fat content and distribution between FAP patients and healthy subjects. METHODS: Body fat content and distribution were measured through Double Energy X-ray Densitometry (DXA) in two groups. Group 1 consisted of 43 Familial Amyloidotic Polyneuropathy patients (19 males, 32 + 8 Yrs, and 24 females, 37 + 5 yrs), who had liver transplant less than 2 months before. Group 2 consisted of 18 healthy subjects of similar age (8 males, 36 + 7 yrs, and 10 females, 39 + 5 yrs). RESULTS: Healthy subjects showed higher values than FAP patients for: BMI (24,2+2,3kg/m2 vs 22,3+3,8 kg/m2 respectively, p<0,05), % trunk BF (26,21+8,34kg vs 20,78+9,05kg respectively, p<0,05), % visceral BF (24,43+7,97% vs 19,21+9,30% respectively, p<0,05), % abdominal BF (26,63+8,51% vs 20,63+10,35% respectively, p<0,05) abdominal subcutaneous BF (0,533+0,421kg vs 0,353+0,257kg respectively, p=0,05), abdominal BF/BF ratio (0,09+0,02 vs 0,08+0,02 respectively, p<0,05) and abdominal BF/trunk BF ratio (0,19+0,03 vs 0,17+0,03 respectively, p<0,05). CONCLUSIONS: These results showed that FAP patients soon after liver transplantation exhibited a healthier body fat profile compared to controls. However, fat content and distribution varied widely in FAP subjects, suggesting an individualized approach for assessment and intervention rather than general guidelines. Future research is needed to investigate the long term consequences on body fat following liver transplant in this population.

Comparison of body fat content and distribution of familial amyloidotic polyneuropathy patients versus healthy subjects

The deposition of amyloid fibers at the peripheral nervous system can induce motor neuropathy in Familial Amiloidotic Polyneuropethy (FAP) patients. This produces progressive reductions in functional capacity. The only treatment for FAP is a liver transplant, followed by aggressive medication that can affect patients' metabolism. To our knowledge, there are no data on body fat distribution or comparison between healthy and FAP subjects, which may be important for clinical assessment and management of this disease.

Lightning Data Observed With Lightning Location System in Portugal

This paper presents an investigation into cloud-to-ground lightning activity over the continental territory of Portugal with data collected by the national Lightning Location System. The Lightning Location System in Portugal is first presented. Analyses about geographical, seasonal, and polarity distribution of cloud-to-ground lightning activity and cumulative probability of peak current are carried out. An overall ground flash density map is constructed from the database, which contains the information of more than five years and almost four million records. This map is compared with the thunderstorm days map, produced by the Portuguese Institute of Meteorology, and with the orographic map of Portugal. Finally, conclusions are duly drawn.

GA topology optimization using random keys for tree encoding of structures

Topology optimization consists in finding the spatial distribution of a given total volume of material for the resulting structure to have some optimal property, for instance, maximization of structural stiffness or maximization of the fundamental eigenfrequency. In this paper a Genetic Algorithm (GA) employing a representation method based on trees is developed to generate initial feasible individuals that remain feasible upon crossover and mutation and as such do not require any repairing operator to ensure feasibility. Several application examples are studied involving the topology optimization of structures where the objective functions is the maximization of the stiffness and the maximization of the first and the second eigenfrequencies of a plate, all cases having a prescribed material volume constraint.

Epidemiology of malaria, schistosomiasis, geohelminths, anemia and malnutrition in the context of a demographic surveillance system in Northern Angola

Background: Malaria, schistosomiasis and geohelminth infection are linked to maternal and child morbidity and mortality in sub-Saharan Africa. Knowing the prevalence levels of these infections is vital to guide governments towards the implementation of successful and cost-effective disease control initiatives. Methodology/Principal Findings: A cross-sectional study of 1,237 preschool children (0–5 year olds), 1,142 school-aged children (6–15 year olds) and 960 women (.15 year olds) was conducted to understand the distribution of malnutrition, anemia, malaria, schistosomiasis (intestinal and urinary) and geohelminths in a north-western province of Angola. We used a recent demographic surveillance system (DSS) database to select and recruit suitable households. Malnutrition was common among children (23.3% under-weight, 9.9% wasting and 32.2% stunting), and anemia was found to be a severe public health problem (i.e., .40%). Malaria prevalence was highest among preschool children reaching 20.2%. Microhematuria prevalence levels reached 10.0% of preschool children, 16.6% of school-aged children and 21.7% of mothers. Geohelminth infections were common, affecting 22.3% of preschool children, 31.6% of school-aged children and 28.0% of mothers. Conclusions: Here we report prevalence levels of malaria, schistosomiasis and geohelminths; all endemic in this poorly described area where a DSS has been recently established. Furthermore we found evidence that the studied infections are associated with the observed levels of anemia and malnutrition, which can justify the implementation of integrated interventions for the control of these diseases and morbidities.

A risk-averse optimization model for trading wind energy in a market environment under uncertainty

In this paper, a stochastic programming approach is proposed for trading wind energy in a market environment under uncertainty. Uncertainty in the energy market prices is the main cause of high volatility of profits achieved by power producers. The volatile and intermittent nature of wind energy represents another source of uncertainty. Hence, each uncertain parameter is modeled by scenarios, where each scenario represents a plausible realization of the uncertain parameters with an associated occurrence probability. Also, an appropriate risk measurement is considered. The proposed approach is applied on a realistic case study, based on a wind farm in Portugal. Finally, conclusions are duly drawn. (C) 2011 Elsevier Ltd. All rights reserved.

Smart Electric Vehicle Charging System

In this work is proposed the design of a system to create and handle Electric Vehicles (EV) charging procedures, based on intelligent process. Due to the electrical power distribution network limitation and absence of smart meter devices, Electric Vehicles charging should be performed in a balanced way, taking into account past experience, weather information based on data mining, and simulation approaches. In order to allow information exchange and to help user mobility, it was also created a mobile application to assist the EV driver on these processes. This proposed Smart ElectricVehicle Charging System uses Vehicle-to-Grid (V2G) technology, in order to connect Electric Vehicles and also renewable energy sources to Smart Grids (SG). This system also explores the new paradigm of Electrical Markets (EM), with deregulation of electricity production and use, in order to obtain the best conditions for commercializing electrical energy.

Comparison of inverse planning systems based on biological or physical factors: Pinnacle®, Corvus® and Monaco®

Radiotherapy (RT) is one of the most important approaches in the treatment of cancer and its performance can be improved in three different ways: through the optimization of the dose distribution, by the use of different irradiation techniques or through the study of radiobiological initiatives. The first is purely physical because is related to the physical dose distributiuon. The others are purely radiobiological because they increase the differential effect between the tumour and the health tissues. The Treatment Planning Systems (TPS) are used in RT to create dose distributions with the purpose to maximize the tumoral control and minimize the complications in the healthy tissues. The inverse planning uses dose optimization techniques that satisfy the criteria specified by the user, regarding the target and the organs at risk (OAR’s). The dose optimization is possible through the analysis of dose-volume histograms (DVH) and with the use of computed tomography, magnetic resonance and other digital image techniques.