20 resultados para Particle and pore radii distributions

em Universidade Federal do Rio Grande do Norte(UFRN)


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Deep bed filtration occurs in several industrial and environmental processes like water filtration and soil contamination. In petroleum industry, deep bed filtration occurs near to injection wells during water injection, causing injectivity reduction. It also takes place during well drilling, sand production control, produced water disposal in aquifers, etc. The particle capture in porous media can be caused by different physical mechanisms (size exclusion, electrical forces, bridging, gravity, etc). A statistical model for filtration in porous media is proposed and analytical solutions for suspended and retained particles are derived. The model, which incorporates particle retention probability, is compared with the classical deep bed filtration model allowing a physical interpretation of the filtration coefficients. Comparison of the obtained analytical solutions for the proposed model with the classical model solutions allows concluding that the larger the particle capture probability, the larger the discrepancy between the proposed and the classical models

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Deep bed filtration occurs in several industrial and environmental processes like water filtration and soil contamination. In petroleum industry, deep bed filtration occurs near to injection wells during water injection, causing injectivity reduction. It also takes place during well drilling, sand production control, produced water disposal in aquifers, etc. The particle capture in porous media can be caused by different physical mechanisms (size exclusion, electrical forces, bridging, gravity, etc). A statistical model for filtration in porous media is proposed and analytical solutions for suspended and retained particles are derived. The model, which incorporates particle retention probability, is compared with the classical deep bed filtration model allowing a physical interpretation of the filtration coefficients. Comparison of the obtained analytical solutions for the proposed model with the classical model solutions allows concluding that the larger the particle capture probability, the larger the discrepancy between the proposed and the classical models

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Modeling transport of particulate suspensions in porous media is essential for understanding various processes of industrial and scientific interest. During these processes, particles are retained due to mechanisms like size exclusion (straining), adsorption, sedimentation and diffusion. In this thesis, a mathematical model is proposed and analytical solutions are obtained. The obtained analytic solutions for the proposed model, which takes pore and particle size distributions into account, were applied to predict the particle retention, pore blocking and permeability reduction during dead-end microfiltration in membranes. Various scenarios, considering different particle and pore size distributions were studied. The obtained results showed that pore blocking and permeability reduction are highly influenced by the initial pore and particle size distributions. This feature was observed even when different initial pore and particle size distributions with the same average pore size and injected particle size were considered. Finally, a mathematical model for predicting equivalent permeability in porous media during particle retention (and pore blocking) is proposed and the obtained solutions were applied to study permeability decline in different scenarios

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Modeling transport of particulate suspensions in porous media is essential for understanding various processes of industrial and scientific interest. During these processes, particles are retained due to mechanisms like size exclusion (straining), adsorption, sedimentation and diffusion. In this thesis, a mathematical model is proposed and analytical solutions are obtained. The obtained analytic solutions for the proposed model, which takes pore and particle size distributions into account, were applied to predict the particle retention, pore blocking and permeability reduction during dead-end microfiltration in membranes. Various scenarios, considering different particle and pore size distributions were studied. The obtained results showed that pore blocking and permeability reduction are highly influenced by the initial pore and particle size distributions. This feature was observed even when different initial pore and particle size distributions with the same average pore size and injected particle size were considered. Finally, a mathematical model for predicting equivalent permeability in porous media during particle retention (and pore blocking) is proposed and the obtained solutions were applied to study permeability decline in different scenarios

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Injectivity decline, which can be caused by particle retention, generally occurs during water injection or reinjection in oil fields. Several mechanisms, including straining, are responsible for particle retention and pore blocking causing formation damage and injectivity decline. Predicting formation damage and injectivity decline is essential in waterflooding projects. The Classic Model (CM), which incorporates filtration coefficients and formation damage functions, has been widely used to predict injectivity decline. However, various authors have reported significant discrepancies between Classical Model and experimental results, motivating the development of deep bed filtration models considering multiple particle retention mechanisms (Santos & Barros, 2010; SBM). In this dissertation, inverse problem solution was studied and a software for experimental data treatment was developed. Finally, experimental data were fitted using both the CM and SBM. The results showed that, depending on the formation damage function, the predictions for injectivity decline using CM and SBM models can be significantly different

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Discrepancies between classical model predictions and experimental data for deep bed filtration have been reported by various authors. In order to understand these discrepancies, an analytic continuum model for deep bed filtration is proposed. In this model, a filter coefficient is attributed to each distinct retention mechanism (straining, diffusion, gravity interception, etc.). It was shown that these coefficients generally cannot be merged into an effective filter coefficient, as considered in the classical model. Furthermore, the derived analytic solutions for the proposed model were applied for fitting experimental data, and a very good agreement between experimental data and proposed model predictions were obtained. Comparison of the obtained results with empirical correlations allowed identifying the dominant retention mechanisms. In addition, it was shown that the larger the ratio of particle to pore sizes, the more intensive the straining mechanism and the larger the discrepancies between experimental data and classical model predictions. The classical model and proposed model were compared via statistical analysis. The obtained p values allow concluding that the proposed model should be preferred especially when straining plays an important role. In addition, deep bed filtration with finite retention capacity was studied. This work also involves the study of filtration of particles through porous media with a finite capacity of filtration. It was observed, in this case, that is necessary to consider changes in the boundary conditions through time evolution. It was obtained a solution for such a model using different functions of filtration coefficients. Besides that, it was shown how to build a solution for any filtration coefficient. It was seen that, even considering the same filtration coefficient, the classic model and the one here propposed, show different predictions for the concentration of particles retained in the porous media and for the suspended particles at the exit of the media

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The diatomite is a natural material that has numerous applications due to changes in their physical and chemical properties after processing. It is currently used in the industry as a sound insulator , filter aid and industrial load . The filter material shall be inert chemical composition , which will diatomite confers a high commercial value and performance not found in other particulate materials , for this application. The diatomite surface undergoes changes after thermal treatment at high temperatures , from 800ºC , with properties that enable its application in the food , beverage , pharmaceutical , cosmetic and textiles . In this work , we developed a study on thermal treatment on natural diatomite to adapt their properties to the application as a filter aid . The heat treatments were performed in an open oven at temperatures of 800ºC , 1000ºC and 1200ºC for a time of 24 hours. Reagents were added in the constitution of the samples analyzed. The reagents used were sodium carbonate (Na2CO3 ) and sodium chloride (NaCl) . The samples were characterized by x - ray diffraction , x -ray fluorescence , scanning electron microscopy , analysis and particle size distribution , specific surface area by the BET method , and pore volume by BJH method. The results showed a reduction in porosity of the material as well as a significant increase in specific surface area after heat treatment and the reactants in the ratio of 3 wt%. The diatomaceous earth , after heat treatment , undergone changes in its coloration , varying in white, cream and beige , which directly interferes with the speed of filtration materials process. All results obtained before and after heat treatment of the material with the values obtained for samples already used industrially , Brazilian and American industry , which were characterized using the same test methods performed with the samples in the study were compared and showed promising efficiency when material studied in the region of Punaú - RN , after processing , reagent addition and heat treatment, as an element in the composition of filter .

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Water injection in oil reservoirs is a recovery technique widely used for oil recovery. However, the injected water contains suspended particles that can be trapped, causing formation damage and injectivity decline. In such cases, it is necessary to stimulate the damaged formation looking forward to restore the injectivity of the injection wells. Injectivity decline causes a major negative impact to the economy of oil production, which is why, it is important to foresee the injectivity behavior for a good waterflooding management project. Mathematical models for injectivity losses allow studying the effect of the injected water quality, also the well and formation characteristics. Therefore, a mathematical model of injectivity losses for perforated injection wells was developed. The scientific novelty of this work relates to the modeling and prediction of injectivity decline in perforated injection wells, considering deep filtration and the formation of external cake in spheroidal perforations. The classic modeling for deep filtration was rewritten using spheroidal coordinates. The solution to the concentration of suspended particles was obtained analytically and the concentration of the retained particles, which cause formation damage, was solved numerically. The acquisition of the solution to impedance assumed a constant injection rate and the modified Darcy´s Law, defined as being the inverse of the normalized injectivity by the inverse of the initial injectivity. Finally, classic linear flow injectivity tests were performed within Berea sandstone samples, and within perforated samples. The parameters of the model, filtration and formation damage coefficients, obtained from the data, were used to verify the proposed modeling. The simulations showed a good fit to the experimental data, it was observed that the ratio between the particle size and pore has a large influence on the behavior of injectivity decline.

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Injectivity decline, which can be caused by particle retention, generally occurs during water injection or reinjection in oil fields. Several mechanisms, including straining, are responsible for particle retention and pore blocking causing formation damage and injectivity decline. Predicting formation damage and injectivity decline is essential in waterflooding projects. The Classic Model (CM), which incorporates filtration coefficients and formation damage functions, has been widely used to predict injectivity decline. However, various authors have reported significant discrepancies between Classical Model and experimental results, motivating the development of deep bed filtration models considering multiple particle retention mechanisms (Santos & Barros, 2010; SBM). In this dissertation, inverse problem solution was studied and a software for experimental data treatment was developed. Finally, experimental data were fitted using both the CM and SBM. The results showed that, depending on the formation damage function, the predictions for injectivity decline using CM and SBM models can be significantly different

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Discrepancies between classical model predictions and experimental data for deep bed filtration have been reported by various authors. In order to understand these discrepancies, an analytic continuum model for deep bed filtration is proposed. In this model, a filter coefficient is attributed to each distinct retention mechanism (straining, diffusion, gravity interception, etc.). It was shown that these coefficients generally cannot be merged into an effective filter coefficient, as considered in the classical model. Furthermore, the derived analytic solutions for the proposed model were applied for fitting experimental data, and a very good agreement between experimental data and proposed model predictions were obtained. Comparison of the obtained results with empirical correlations allowed identifying the dominant retention mechanisms. In addition, it was shown that the larger the ratio of particle to pore sizes, the more intensive the straining mechanism and the larger the discrepancies between experimental data and classical model predictions. The classical model and proposed model were compared via statistical analysis. The obtained p values allow concluding that the proposed model should be preferred especially when straining plays an important role. In addition, deep bed filtration with finite retention capacity was studied. This work also involves the study of filtration of particles through porous media with a finite capacity of filtration. It was observed, in this case, that is necessary to consider changes in the boundary conditions through time evolution. It was obtained a solution for such a model using different functions of filtration coefficients. Besides that, it was shown how to build a solution for any filtration coefficient. It was seen that, even considering the same filtration coefficient, the classic model and the one here propposed, show different predictions for the concentration of particles retained in the porous media and for the suspended particles at the exit of the media

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ALVES, Ana paula Melo. Vermiculitas tratadas quimicamente na obtenção de sólidos microporosos como precursores para híbridos inorgânico-orgânicos com aplicações adsortivas. 2009. 124 f. Tese (Doutorado em Quimica) - Centro de Ciências Exatas e da Natureza, Universidade Federal da Paraíba, João Pessoa, PB, 2009.

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Na unfolding method of linear intercept distributions and secction área distribution was implemented for structures with spherical grains. Although the unfolding routine depends on the grain shape, structures with spheroidal grains can also be treated by this routine. Grains of non-spheroidal shape can be treated only as approximation. A software was developed with two parts. The first part calculates the probability matrix. The second part uses this matrix and minimizes the chi-square. The results are presented with any number of size classes as required. The probability matrix was determined by means of the linear intercept and section area distributions created by computer simulation. Using curve fittings the probability matrix for spheres of any sizes could be determined. Two kinds of tests were carried out to prove the efficiency of the Technique. The theoretical tests represent ideal cases. The software was able to exactly find the proposed grain size distribution. In the second test, a structure was simulated in computer and images of its slices were used to produce the corresponding linear intercept the section area distributions. These distributions were then unfolded. This test simulates better reality. The results show deviations from the real size distribution. This deviations are caused by statistic fluctuation. The unfolding of the linear intercept distribution works perfectly, but the unfolding of section area distribution does not work due to a failure in the chi-square minimization. The minimization method uses a matrix inversion routine. The matrix generated by this procedure cannot be inverted. Other minimization method must be used

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The addition of active silica potentially improves the quality of concrete due to its high reactivity and pore refinement effect. The reactivity of silica is likely related to its charge density. Variations in surface charge alter the reactivity of the material consequently affecting the properties of concrete. The present study aimed at investigating variations in the charge density of silica as a function of acid treatments using nitric or phosphoric acid and different pH values (2.0, 4.0 and 6.0). Effects on concrete properties including slump, mechanical strength, permeability and chloride corrosion were evaluated. To that end, a statistical analysis was carried out and empirical models that correlate studied parameters (pH, acid and cement) with concrete properties were established. The quality of the models was tested by variance analysis. The results revealed that the addition of silica was efficiency in improving the properties of concrete, especially the electrochemical parameters. The addition of silica treated using nitric acid at pH = 4.0 displayed the best cement performance including highest strength, reduced permeability and lowest corrosion current

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This a study on the achievement of alumina membranes by the method of anodizing. From this method got up a layer of aluminum oxide on the anodic metal, who presented the basic properties necessary for the application as a support for the production and acquisition of nanomaterials, such as porosity nano and resistance to high temperature, and other properties, as resistance to corrosion, and chemical, high ranking of the structure and pore size of the pores. The latter, ranging from 10 to 100nm depended on the electrolyte used, which in this study was the H2SO4. To remove all remaining aluminum, it is a bath of dissolution with HCl and CuCl where the residual aluminum has been withdrawn, and the deep pores were opened after chemical treatment with NaOH. After the dissolution, the membranes were calcined at temperatures of 300, 600 and 900° C, and sintered at temperatures of 1200 and 1300º C to win mechanical strength, porosity and observe the desired crystallization. Then went through analyses of composition through X-ray diffraction and morphology of the microstructure through a scanning electron microscope. The method was effective for obtaining alumine membranes applied in the processes of production of materials in nano

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Porous ceramics have many applications: thermal insulation, catalytic support, materials to fire protection, filters, and others. There are many techniques to production of ceramic filters. One technique to obtain ceramic filters is the replication method. This method consists in the impregnation of polymeric foam with ceramic slurry followed by a heating treatment that will burn out the organic elements and sintering of the material, resulting of a replication of the original foam. To perform their functions ceramic filters must satisfy mechanical requirements and permeability parameters (darcian k1 and no-darcian k2). The permeability and the strength of the ceramic material are dependent of the pore size and pore distribution. To the use at high temperatures the evaluation of mechanical properties in these temperatures is necessary. In this work the mechanical behavior of two commercial porous ceramics (10 and 40 poros per inch) was studied these materials were submitted to compression and four-point flexure test (room temperature, at 1000 °C, after thermal shock). Density and porosity measurements, permeability tests and microstructural analysis by scanning electronic microscopy (SEM) were realized. The Results showed that the decrease of mechanical strength of these materials, when submitted to thermal shock, occur for propagation of new cracks from cracks pre-existing and the permeability depends of the pore size