65 resultados para Algoritmo de Colisão de Partículas
Resumo:
Metal powder sintering appears to be promising option to achieve new physical and mechanical properties combining raw material with new processing improvements. It interest over many years and continue to gain wide industrial application. Stainless steel is a widely accepted material because high corrosion resistance. However stainless steels have poor sinterability and poor wear resistance due to their low hardness. Metal matrix composite (MMC) combining soft metallic matrix reinforced with carbides or oxides has attracted considerable attention for researchers to improve density and hardness in the bulk material. This thesis focuses on processing 316L stainless steel by addition of 3% wt niobium carbide to control grain growth and improve densification and hardness. The starting powder were water atomized stainless steel manufactured for Höganäs (D 50 = 95.0 μm) and NbC produced in the UFRN and supplied by Aesar Alpha Johnson Matthey Company with medium crystallite size 16.39 nm and 80.35 nm respectively. Samples with addition up to 3% of each NbC were mixed and mechanically milled by 3 routes. The route1 (R1) milled in planetary by 2 hours. The routes 2 (R2) and 3 (R3) milled in a conventional mill by 24 and 48 hours. Each milled samples and pure sample were cold compacted uniaxially in a cylindrical steel die (Ø 5 .0 mm) at 700 MPa, carried out in a vacuum furnace, heated at 1290°C, heating rate 20°C stand by 30 and 60 minutes. The samples containing NbC present higher densities and hardness than those without reinforcement. The results show that nanosized NbC particles precipitate on grain boundary. Thus, promote densification eliminating pores, control grain growth and increase the hardness values
Resumo:
The new oil reservoirs discoveries in onshore and ultra deep water offshore fields and complex trajectories require the optimization of procedures to reduce the stops operation during the well drilling, especially because the platforms and equipment high cost, and risks which are inherent to the operation. Among the most important aspects stands out the drilling fluids project and their behavior against different situations that may occur during the process. By means of sedimentation experiments, a correlation has been validated to determe the sedimentation particles velocity in variable viscosity fluids over time, applying the correction due to effective viscosity that is a shear rate and time function. The viscosity evolution over time was obtained by carrying out rheologic tests using a fixed shear rate, small enough to not interfere in the fluid gelling process. With the sedimentation particles velocity and the fluid viscosity over time equations an iterative procedure was proposed to determine the particles displacement over time. These equations were implemented in a case study to simulate the cuttings sedimentation generated in the oil well drilling during stops operation, especially in the connections and tripping, allowing the drilling fluid project in order to maintain the cuttings in suspension, avoiding risks, such as stuck pipe and in more drastic conditions, the loss of the well
Resumo:
With the growth of energy consumption worldwide, conventional reservoirs, the reservoirs called "easy exploration and production" are not meeting the global energy demand. This has led many researchers to develop projects that will address these needs, companies in the oil sector has invested in techniques that helping in locating and drilling wells. One of the techniques employed in oil exploration process is the reverse time migration (RTM), in English, Reverse Time Migration, which is a method of seismic imaging that produces excellent image of the subsurface. It is algorithm based in calculation on the wave equation. RTM is considered one of the most advanced seismic imaging techniques. The economic value of the oil reserves that require RTM to be localized is very high, this means that the development of these algorithms becomes a competitive differentiator for companies seismic processing. But, it requires great computational power, that it still somehow harms its practical success. The objective of this work is to explore the implementation of this algorithm in unconventional architectures, specifically GPUs using the CUDA by making an analysis of the difficulties in developing the same, as well as the performance of the algorithm in the sequential and parallel version
Resumo:
Many challenges have been presented in petroleum industry. One of them is the preventing of fluids influx during drilling and cementing. Gas migration can occur as result of pressure imbalance inside the well when well pressure becomes lower than gas zone pressure and in cementing operation this occurs during cement slurry transition period (solid to fluid). In this work it was developed a methodology to evaluate gas migration during drilling and cementing operations. It was considered gel strength concept and through experimental tests determined gas migration initial time. A mechanistic model was developed to obtain equation that evaluates bubble displacement through the fluid while it gels. Being a time-dependant behavior, dynamic rheological measurements were made to evaluate viscosity along the time. For drilling fluids analyzed it was verified that it is desirable fast and non-progressive gelation in order to reduce gas migration without affect operational window (difference between pore and fracture pressure). For cement slurries analyzed, the most appropriate is that remains fluid for more time below critical gel strength, maintaining hydrostatic pressure above gas zone pressure, and after that gels quickly, reducing gas migration. The model developed simulates previously operational conditions and allow changes in operational and fluids design to obtain a safer condition for well construction
Resumo:
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