Remoção, por flotação, de óleo em águas produzidas na indústria de petróleo: eficiência e modelagem do processo

The separation oil-water by the use of flotation process is characterized by the involvement between the liquid and gas phases. For the comprehension of this process, it s necessary to analyze the physical and chemical properties command float flotation, defining the nature and forces over the particles. The interface chemistry has an important role on the flotation technology once, by dispersion of a gas phase into a liquid mixture the particles desired get stuck into air bubbles, being conduced to a superficial layer where can be physically separated. Through the study of interface interaction involved in the system used for this work, was possible to apply the results in an mathematical model able to determine the probability of flotation using a different view related to petroleum emulsions such as oil-water. The terms of probability of flotation correlate the collision and addition between particles of oil and air bubbles, that as more collisions, better is the probability of flotation. The additional probability was analyzed by the isotherm of absorption from Freundlich, represents itself the add probability between air bubbles and oil particles. The mathematical scheme for float flotation involved the injected air flow, the size of bubbles and quantity for second, the volume of float cell, viscosity of environment and concentration of demulsifier. The results shown that the float agent developed by castor oil, pos pH variation, salt quantity, temperature, concentration and water-oil quantity, presented efficient extraction of oil from water, up to 95%, using concentrations around 11 ppm of demulsifier. The best results were compared to other commercial products, codified by ―W‖ and ―Z‖, being observed an equivalent demulsifier power between Agflot and commercial product ―W‖ and superior to commercial product ―Z‖

Utilizando mapas de conectividade fuzzy no desenvolvimento de algoritmos reparadores de imagens binárias 3D

A 3D binary image is considered well-composed if, and only if, the union of the faces shared by the foreground and background voxels of the image is a surface in R3. Wellcomposed images have some desirable topological properties, which allow us to simplify and optimize algorithms that are widely used in computer graphics, computer vision and image processing. These advantages have fostered the development of algorithms to repair bi-dimensional (2D) and three-dimensional (3D) images that are not well-composed. These algorithms are known as repairing algorithms. In this dissertation, we propose two repairing algorithms, one randomized and one deterministic. Both algorithms are capable of making topological repairs in 3D binary images, producing well-composed images similar to the original images. The key idea behind both algorithms is to iteratively change the assigned color of some points in the input image from 0 (background)to 1 (foreground) until the image becomes well-composed. The points whose colors are changed by the algorithms are chosen according to their values in the fuzzy connectivity map resulting from the image segmentation process. The use of the fuzzy connectivity map ensures that a subset of points chosen by the algorithm at any given iteration is the one with the least affinity with the background among all possible choices