Thesis (Ph. D.)--University of Wisconsin--Madison, 1970. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (Ph. D.)--University of Chicago, 1915. / "Reprinted from the Physical Review, N.S., Vol. VII, no. 1, January, 1916. Includes bibliographical references. Also available on the Internet.

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Thesis (M.Sc. (Applied Mathematics)) -- University of Limpopo, 2008 / Understanding the effects of blood viscosity variation plays a very crucial role in hemodynamics, thrombosis and inflammation and could provide useful information for diagnostics and therapy of (cardio) vascular diseases. Blood viscosity, which arises from frictional interactions between all major blood constituents, i.e. plasma, plasma proteins and red blood cells, constitutes blood inherent resistance to flow in the blood vessel. Generally, blood viscosity in large arteries is lower near the vessel wall due to the presence of plasma layer in this peripheral region than the viscosity in the central core region which depends on the hematocrit. In this dissertation, the flow of blood in a large artery is investigated theoretically using the fluid dynamics equations of continuity and momentum. Treating artery as a rigid channel with uniform width and blood as a variable viscosity incompressible Newtonian fluid, the basic flow structure and its stability to small disturbances are examined. A fourth-order eigenvalue problem which reduces to the well known Orr–Sommerfeld equation in some limiting cases is obtained and solved numerically by a spectral collocation technique with expansions in Chebyshev polynomials implemented in MATLAB. Graphical results for the basic flow axial velocity, disturbance growth rate and marginal stability curve are presented and discussed. It is worth pointing out that, a decrease in plasma viscosity near the arterial wall has a stabilizing effect on the flow.

Predicting reservoir oil viscosity with numerical correlation equations using field-measured variables is widely used in the petroleum industry. Most published correlation equations, however, have never profoundly realized the genuine relationship between the reservoir oil viscosity and other field-measured parameters. Using the proposed systematic strategy is an effective solution for achieving a high performance correlation equation of reservoir oil viscosity. The proposed strategy begins with creating a large database of pressure-volumetemperature (PVT) reports and screening all possible erroneous data. The relationship between the oil viscosity and other field-measured parameters is intensively analyzed by using theoretical and empirical approaches to determine the influential parameters for correlating reservoir oil viscosity equations. The alternating conditional expectation (ACE) algorithm is applied for correlating saturated and undersaturated oil viscosity equations. The precision of field-measured PVT data is inspected by a data reconciliation technique in order to clarify the correctness of oil viscosity correlations. Finally, the performance of the proposed oil viscosity correlation equations is represented in terms of statistical error analysis functions. The result of this study shows that reservoir oil density turns out to be the most effective parameter for correlating both saturated and undersaturated reservoir oil viscosity equations. Expected errors in laboratory-measured oil viscosity are the main factors that degrade the efficiency of oil viscosity correlation equations. The proposed correlation equations provide a reasonable estimate of reservoir oil viscosity; and their superior performance is more reliable than that of published correlation equations at any reservoir conditions.

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