A preservação dos recursos hídricos e seu correto manejo têm sido grandes desafios da atualidade. Uma forma de avaliar a qualidade de um corpo hídrico é através da análise de parâmetros biológicos, físicos e químicos, os quais podem ser convenientemente simulados através de modelos matemáticos e computacionais. Tais ferramentas são bastante úteis, por sua capacidade de geração de cenários que possam embasar, por exemplo, tomadas de decisão. A região de estudo compreendeu o estuário do Rio Macaé, localizado na costa norte do estado do Rio de Janeiro. Com o objetivo de identificar a procedência e magnitude de um hipotético lançamento de poluente nas águas deste estuário, neste trabalho foi implementada a solução do problema de transporte de constituintes e então realizada uma análise de sensibilidade, com o intuito de avaliar a possível identificação da fonte de contaminantes frente ao modelo de transporte. Com os resultados promissores desta análise, foi então aplicado o método estocástico Luus-Jaakola para a estimação da localização da fonte de contaminantes única, pontual e constante. Os estudos permitiram concluir que este método possa ser uma importante ferramenta para a gestão dos recursos hídricos, auxiliando na identificação de possíveis responsáveis por passivos ambientais.
To obtain information about pavement structure, nowadays, destructive prospecting is carried out, interfering significantly with traffic. Proposed here in is a less destructive and invasive technique, whereby a thermal probe with temperature sensors is installed in the pavement. This process identifies the sources of heat to obtain the temperature distribution as a function of time and space at different depths; to solve the heat transfer problem in two dimensions and to estimate the thickness and thermal materials properties of each layer through the Inverse Problem. The Direct Problem has been modeled by a heat conduction equation and solved by Central Finite Differences, using the explicit method of time advancements. The Genetic and Memetic Algorithms have been efficient in estimating the thickness of the layers and they have presented little difference between the estimated values at each application. The proposed technique has been efficient in estimating the thickness in the tests with experimental pavements and it brings a new perspective for structural evaluation, with reduced pavement intervention and traffic interference. Keywords
The quality of a given water body can be assessed through the analysis of a number of indicators. Mathematical and computational models can be built to simulate the behavior of these indicators (observable variables), in such a way that different scenarios can be generated, supporting decisions regarding water resources management. In this study, the transport of a conservative contaminant in an estuarine environment is simulated in order to identify the position and intensity of the contaminant source. For this, it was formulated an inverse problem, which was solved through computational intelligence methods. This approach required adaptations to these methods, which had to be modified to relate the source position to the discrete mesh points of the domain. In this context, two adaptive techniques were developed. In one, the estimated points are projected to the grid points, and in the other, points are randomly selected in the iterative search spaces of the methods. The results showed that the methodology here developed has a strong potential in water bodies’ management and simulation.
This work aims to investigate the potential of combining the Mathematical Modeling methodology with the use of the software Tracker with undergraduate students in Mathematics in the reconstruction of physical models for the construction of function concepts. For this, a qualitative and exploratory study of bibliographic and experimental character was carried out, involving field activities. Our results point to a greater understanding in the construction of the models, since the mathematical models can be recreated from the correlation to physical models already validated. We also verified that the Tracker software enables an excellent visual perception of different concept images.
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