No description available.

This work is concerned with the application of finite difference simulation to modelling the pressure response in partially penetrating oil wells. This has relevance to the oil and hydrology industries where pressure behaviour is used to infer the nature of aquifer or reservoir properties, particularly permeability. In the case of partially penetrating wells, the pressure response carries information regarding the magnitude of permeability in the vertical direction, a parameter that can be difficult to measure by other means and one that has a direct influence on both the total volumes of oil that can be recovered and on the rate of recovery. The derivation of the non-linear differential equations that form the basis for multiphase fluid flow in porous media is reviewed and it is shown how they can be converted into a set of finite difference equations. Techniques used to solve these equations are explained, with particular emphasis on the approach followed by the commercial simulation package used in this study. This involves use of Newton's method to linearize the equations followed by application of a pre-conditioned successive minimization technique to solve the resulting linear equations. Finite difference simulation is applied to a hypothetical problem of solving pressure response in a partially penetrating well in an homogenous but anisotropic medium and the results compared with those from analytical solutions. Differences between the results are resolved, demonstrating that the required level of accuracy can be achieved through selective use of sufficiently small grid blocks and time-steps. Residual discrepancies with some of the analytical methods can be traced to differences in the boundary conditions used in their derivation. The simulation method is applied to matching a complex real-life well test with vertical and lateral variation in properties (including fluid saturation). An accurate match can be achieved through judicious adjustment of the problem parameters with the proviso that the vertical permeability needs to be high. This suggests that the recovery mechanism in the oil field concerned can be expected to be highly efficient, something that has recently been confirmed by production results. / Thesis (M.Sc.)-University of Natal, Pietermaritzburg, 2002.

Thesis (MScEng (Mathematical Sciences. Applied Mathematics))--University of Stellenbosch, 2006. / An analytical modelling procedure for predicting the streamwise pressure gradient for steady laminar incompressible flow of a Newtonian fluid through homogeneous isotropic granular porous media is introduced. The modelling strategy involves the spatial volume averaging of a statistical representative portion of the porous domain to obtain measurable macroscopic quantities from which macroscopic transport equations can be derived. A simple pore-scale model is introduced to approximate the actual complex granular porous microstructure through rectangular cubic geometry. The sound physical principles on which the modelling procedure is based avoid the need for redundant empirical coefficients. The model is generalized to predict the rheological flow behaviour of non-Newtonian purely viscous power law fluids by introducing the dependence of the apparent viscosity on the shear rate through the wall shear stress. The field of application of the Newtonian model is extended to predict the flow behaviour in fluidized beds by adjusting the Darcy velocity to incorporate the relative velocity of the solid phase. The Newtonian model is furthermore adjusted to predict fluid flow through Fontainebleau sandstone by taking into account the effect of blocked throats at very low porosities. The analytical model as well as the model generalizations for extended applicability is verified through comparison with other analytical and semi-empirical models and a wide range of experimental data from the literature. The accuracy of the predictive analytical model reveals to be highly acceptable for most engineering designs.

Thesis (MSc (Mathematical Sciences. Applied Mathematics))--University of Stellenbosch, 2007. / The understanding and quantitative description of fluid flowthrough porousmedia, is a science which has been going on for many years and investigated in a variety of disciplines. Studies in this field have primarily been based on models, which can either be described as empirical or theoretical. Part of the current study is to understand fluid flow in porous media through studying three recent theoretical pore-scale models based on the concept of a Representative Unit Cell (RUC), to represent a porous medium. Amongst other assumptions, these models assumed plane Poiseuille flow throughout each pore section of a rectangular RUC. The main objective of this study is to numerically verify this assumption using Computational Fluid Dynamics (CFD) software, FLUENT version 6.2.16. Attention is also paid to comparison between these models with the experimental data, obtained during the model tests of airflow through a timber stack end, undertaken in a wind tunnel. The laminar and intermediate airflow through a timber stack end is simulated using the commercial software FLUENT, and the results are validated against the theoretical pore-scale models and experimental data. Two turbulence models which are, the Standard k − e and Reynolds-Stress models are used in these computations, the aimbeing to determine howwell they are able to reproduce the experimental data. The numerical results are in good agreement with one of the theoretical models presented and the experimental data.

Orientador: Hyun Mo Yang / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica / Made available in DSpace on 2018-08-05T18:54:32Z (GMT). No. of bitstreams: 1 Rosales_JuanCarlos_M.pdf: 1360240 bytes, checksum: 84fee5e0958180b35a0f098cc5b87f4d (MD5) Previous issue date: 2005 / Resumo: Neste trabalho fizemos a modelagem da leishmaniose começando com o ciclo doméstico ou urbano com 2-hospedeiros para estender os resultados ao ciclo peridoméstico com n-hospedeiros. No caso urbano, consideramos a população do vetor constante e, após, com capacidade de suporte. Simplificamos o modelo para analisar um dos fatores de risco da leishmaniose, o desmatamento. Derivamos as expressões correspondentes ao número de reprodutibilidade basal em todos os casos por meio de análise de estabilidade. Realizamos simulações com dados de zonas endêmicas. Ao final aplicamos a análise de sensitividade para o número de reprodutibilidade basal para o caso de 2-hospedeiros / Abstract: We are dealing with a modelling of leishmaniasis considering initially the urban cycle with 2-hosts aiming to extend the results to a peridomestic cycle for n-hosts. In the urban case we consider the vector population constant, also, variable. We simplify the model the assess the factor regarded to risk of leishmaniasis analysis, which is the deforestation. We derive the expression for the basic reproduction number from the stability analysis. The model was simulated whit respect to endemics zone. Finally we performed the sensibility analysis of the basic reproduction number to the case of 2-hosts / Mestrado / Epidemiologia Matematica. Biomatematica / Mestre em Matemática Aplicada

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Meteorology and Physical Oceanography, 1982. / Microfiche copy available in Archives and Science / Bibliography: leaves 108-109. / by Lawrence J. Pratt. / Ph.D.

In an emerging energy landscape that increasingly discourages the use of traditional fossil fuels, there remain applications for which the continued use of high energy density liquid fuels is required, such as aviation and other uses where space and weight are critical design factors, or long term energy storage where cost and long term availability are required. To achieve this while transitioning to green sources of energy requires the design of next-generation combustion engines that can burn alternative fuels such as bio-derived or synthetic fuels; this process will be heavily dependent on design tools such as computational fluid dynamics packages, underpinned by accurate chemical kinetic models for the fuels in question. These kinetic models often contain thermodynamic information about hundreds of unique chemical species and thousands of chemical reactions forming an interconnected network between species governing their rates of production and destruction. Historically, generation of such high-fidelity kinetic models has required decades of research---too long for the engines that will require advanced fuels. Development of a kinetic model that is predictive of certain quantities of interest (ignition delay times, flame speeds, etc) can broadly be broken into four distinct stages: 1) initial ``crude'' model generation, 2) experimental design, 3) experiments and ab-initio theory calculations, and 4) kinetic model optimization. Advances in data-enabled science and ever-increasing computing power have offered pathways towards eventually automating this process. This work aims to introduce a collection of tools and building blocks that will assist in the overall aim of automatic kinetic model development, and in doing so fill important gaps in the current capabilities available in the literature. In particular, the work here touches on aspects of all four of the stages in the model development process described above. With regard to 1), while there are tools available in the literature for automatic generation of kinetic models for an increasingly large library of fuels, these models remain subject to the constraints imposed by current chemical kinetic model structures and combustion codes. Here, automatic screening procedures are introduced that investigate the impact on kinetic model prediction errors due to two distinct issues related to pressure-dependent chemistry: the lack of a new class of chemical reaction type in current chemical kinetic models, and effects due to how species-specific energy transfer parameters are represented in pressure-dependent stabilization reactions within kinetic models. With regard to 2) and 3), a Bayesian optimal experimental design algorithm is paired with computer-controllable perfectly-stirred reactor experiments with unique capability to both explore a combinatorically complex experiment parameter space (including flowing up to ten unique gas mixtures simultaneously) and measure dozens of chemical species using rapid, on-line diagnostics. This setup allows for key reaction pathways to be carefully "sensitized'' with the addition of trace quantities of key chemical species, a capability that has not been used elsewhere in literature. Generally speaking, other experimental design algorithms in literature have not explored experimental design spaces that are radically different from those used by experienced researchers in their manual experimental design processes, and the complexity of the mixtures explored by most traditional combustion experiments is limited to two or three different chemical species at most. The sensitization of key reaction pathways unlocks the ability to perform truly transformational parameter inferences with minimal amounts of experimental data. With regard to joining step 3) to 4) in the above process, semi-automated post-processing codes allow for rapid optimizations to be performed for a prior kinetic model on the basis of experiments chosen by our experimental design algorithm. Critically, a combination of the experimental design algorithm developed here and the jet-stirred reactor experiments described was tested on the kinetic model for N₂O decomposition, which has uncertainties for key reaction rates that have persisted for decades (indeed, researchers suggest kinetic rate constants for N₂O+O=N₂+O₂ that differ by at least four orders of magnitude!). Optimizations using the Multi-Scale Informatics (MSI) tool developed by our research group were run on the basis of experimental data obtained in the aforementioned experiments, and used to gain insights about the rate constant for a key reaction in N₂O decomposition chemistry, N₂O+O=N₂+O₂ , serving as a proof-of-concept for key portions of what will form the backbone of an automatic kinetic model development pipeline.

No description available.

Comparisons were made on the behavior of two full-sized reticulated domes subjected to uniform static loads only and uniform static loads with earthquake excitations. Space truss elements were used in the dome models. The stiffness matrix of the space truss element allows for the nonlinear strain-displacement behavior and the stress-strain behavior of the material is modeled with a bilinear approximation. The nonlinear solution technique is the Newton-Raphson method while the direct integration technique is the Newmark- Beta method. The joint displacements for the static and the dynamic analyses were compared for both domes along with the axial stresses in all members. The percentage increases in the axial stresses of the dynamic analyses as compared to those of the static analyses were determined. The reticulated domes used in the study were found to bet capable of withstanding the earthquake excitations when subjected to various uniform loads without failure. / Master of Science

The intent of this study is to develop an algorithm for structural design based on allowable displacements for structural members, independent of stresses caused by the configurations imposed. Structural design can be based on displacement constraints applied in the same basic format as stress constraints so that convergence is based on allowable displacements rather than on stresses. / Master of Science