Estudo numérico do impacto das emissões veiculares e fixas da cidade de Manaus nas concentrações de poluentes atmosféricos da região amazônica

The main aim of this study was to evaluate the impact of the urban pollution plume from the city of Manaus by emissions from mobile and stationary sources in the atmospheric pollutants concentrations of the Amazon region, by using The Weather Research and Forecasting with Chemistry (WRF-Chem) model. The air pollutants analyzed were CO, NOx, SO2, O3, PM2.5, PM10 and VOCs. The model simulations have been configured with a grid spacing of 3 km, with 190 x and 136 y grid points in horizontal spacing, centered in the city of Manaus during the period of 17 and 18 of March 2014. The anthropogenic emissions inventories have gathered from mobile sources that were estimated the emissions of light and heavy-duty vehicles classes. In addition, the stationary sources have considered the thermal power plants by the type of energy sources used in the region as well as the emissions from the refinery located in Manaus. Various scenarios have been defined with numerical experiments that considered only emissions by biogenic, mobile and stationary sources, and replacement fuel from thermal power plant, along with a future scenario consisting with twice as much anthropogenic emissions. A qualitative assessment of simulation with base scenario has also been carried out, which represents the conditions of the region in its current state, where several statistical methods were used in order to compare the results of air pollutants and meteorological fields with observed ground-based data located in various points in the study grid. The qualitative analysis showed that the model represents satisfactorily the variables analyzed from the point of view of the adopted parameters. Regarding the simulations, defined from the base scenarios, the numerical experiments indicate relevant results such as: it was found that the stationary sources scenario, where the thermal power plants are predominant, resulted in the highest concentrations, for all air pollutants evaluated, except for carbon monoxide when compared to the vehicle emissions scenario; The replacement of the energy matrix of current thermal power plants for natural gas have showed significant reductions in pollutants analyzed, for instance, 63% reductions of NOx in the contribution of average concentration in the study grid; A significant increase in the concentrations of chemical species was observed in a futuristic scenario, reaching up to a 81% increase in peak concentrations of SO2 in the study area. The spatial distributions of the scenarios have showed that the air pollution plume from Manaus is predominantly west and southwest, where it can reach hundreds of kilometers to areas dominated by original soil covering.

Sensoriamento óptico quase-distribuído aplicado ao monitoramento de trocadores de calor de usinas hidrelétricas

This work aims to develop optical sensors for temperature monitoring in hydroelectric power plant heat exchangers. The proposed sensors are based on the Fiber Bragg Gratings technology. First of all, a prototype with three sensors inscribed in a same fiber was developed. This fiber was then fixed to a conventional Pt100 sensor rod and inserted in a thermowell. The ensemble was then calibrated in a workbench, presenting a maximum combined uncertainty of 2,06 °C. The sensor was installed in one of the heat exchangers of the Salto Osório’s hydroelectric power plant. This power plant is situated in the Iguaçu river, at the Paraná state. Despite the satisfactory results, the sensor was improved to a second version. In this, fifteen optical Bragg sensors were inscribed in a same fiber. The fixation with a conventional sensor was no longer necessary, because the first version results comproved the efficiency and response time in comparison to a conventional sensor. For this reason, it was decided to position the fiber inside a stainless steel rod, due to his low thermal expansion coefficient and high corrosion immunity. The utilization of fifteen fiber Bragg gratings aims to improve the sensor spatial resolution. Therefore, measurements every ten centimeters with respect to the heat exchanger’s height are possible. This provides the generation of a thermal map of the heat exchanger’s surface, which can be used for determination of possible points of obstruction in the hydraulic circuit of the heat exchanger. The heat exchanger’s obstruction in hydroelectric power plants usually occur by bio-fouling, and has direct influence in the generator’s cooling system efficiency. The obtained results have demonstrated the feasibility in application of the optical sensors technology in hydroelectric power plants.

Diagnóstico automático de eventos e distúrbios em unidades geradoras e usinas utilizando lógica fuzzy

The electric power systems are getting more complex and covering larger areas day by day. This fact has been contribuiting to the development of monitoring techniques that aim to help the analysis, control and planning of power systems. Supervisory Control and Data Acquisition (SCADA) systems, Wide Area Measurement Systems and disturbance record systems. Unlike SCADA and WAMS, disturbance record systems are mainly used for offilne analysis in occurrences where a fault resulted in tripping of and apparatus such as a transimission line, transformer, generator and so on. The device responsible for record the disturbances is called Digital Fault Recorder (DFR) and records, basically, electrical quantities as voltage and currents and also, records digital information from protection system devices. Generally, in power plants, all the DFRs data are centralized in the utility data centre and it results in an excess of data that difficults the task of analysis by the specialist engineers. This dissertation shows a new methodology for automated analysis of disturbances in power plants. A fuzzy reasoning system is proposed to deal with the data from the DFRs. The objective of the system is to help the engineer resposnible for the analysis of the DFRs’s information by means of a pre-classification of data. For that, the fuzzy system is responsible for generating unit operational state diagnosis and fault classification.