No description available.

Thesis (Ph. D.)--University of Hawaii at Manoa, 1995. / Includes bibliographical references (leaves 162-166). / Microfiche. / 166 leaves, bound ill. 29 cm

Rock physical properties are usually associated with important geologic features within mineral deposits and can be used to define the location, depth and size of the deposit, type of ore, or physical property contrast between the host and country rock. Geophysical surveys are sensitive to physical properties and therefore are widely used in mining exploration, especially in concealed terrains. The surveys can be performed at multiple scales, resulting in corresponding physical property datasets at different scales. Survey scale can vary from core or hand sample, involving few cubic centimeters, to regional-scale surveys providing information about physical property contrasts between distinct regional geological features. The understanding of the relationship between the physical property distributions with the sample volume (e.g. district, deposit, and drill-hole scale) is required where point scale physical property measurements are going to be consistent with measurements at larger volumetric scales during the integration of data for geophysical modeling The approach used to address the problem of understanding the scaling relations of physical properties, was achieved by considering them as second order stationary regionalized variables and then applying the random function formalism, provided by geostatistics theory. Geostatistics provide the required framework to characterize, quantify, model and link the spatial variability of the random variable at the different volumetric scales. The aim of this study is to apply geostatistics to effectively integrate data collected at several scales and bring knowledge to the understanding of the scaling relations of magnetic susceptibility. For this purpose, measurements of magnetic susceptibility available from Flin Flon copper-zinc district in Canada will be used. The data available at point scale were collected with hand portable magnetic susceptibility meter. The larger volumetric scale dataset were acquired using frequency domain electromagnetic instruments capable of measuring larger sample volumes, and then used to obtain magnetic susceptibility models using geophysical inversion algorithms. Once different scale models of magnetic susceptibility were available, quantification of the scaling relation using geostatistics, specifically variogram models and dispersion variance were determined. The understanding provided by the scaling analysis of the Flin-Flon magnetic data is applied to data from the Rio Blanco copper district in central Chile. Magnetic susceptibility measurements collected with a hand magnetic susceptibility meter on drill-core is integrated in larger scale volumes used for geophysical inversion modeling of regional scale airborne magnetic field measurements to recover magnetic susceptibility models. The methodology resulting from this application of geostatistics is used to address the problem of integrating multiple scales of physical property data in an effective way. The resulting physical property models capture the small-scale magnetic susceptibility variability observed and can guide larger-scale variability within geophysical inversion models. Establishing reliable statistical correlations between physical properties and rock units controlling ore within deposits are crucial steps leading predictive mine exploration tools. Any numerical modeling approach to establish these correlations should consider in some way the scaling nature of both physical property and ore content.

Thesis (M.A.)--University of Missouri-Columbia, 2007. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on November 6, 2007) Includes bibliographical references.

Thesis (Ph. D.)--University of Toronto, 2004. / Adviser: Shizuhiko Nishisato.

Thesis (Ph.D.)--University of Missouri-Columbia, 2005. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (Novembr 15, 2006) Vita. Includes bibliographical references.

AN ABSTRACT OF THE THESIS OF John Goodloe, for the Master of Science degree in Mechanical Engineering, presented on April 13, 2016, at Southern Illinois University Carbondale. TITLE: STANDARDIZED SUB-SCALE DYNAMOMETER SCALING METHOD FOR TRANSIT AND FREIGHT TRAIN APPLICATIONS MAJOR PROFESSOR: Dr. Peter Filip Dynamometers are machines that are used in several industries for measuring force, torque, or power of a mechanism. These devices are in fact very useful in the friction material industry. Friction materials are created and then tested on dynamometers to analyze physical properties such as the dynamic coefficient of friction of the material based upon its retarding force against the wheel or disc, which is mounted to the dynamometer drive shaft. Dynamometer testing is expensive and often time consuming. Sub-scale dynamometers may be used to reduce cost, time, and material use while providing similar test results by implementing a proper scaling method. There are several scaling methods, but this approach will use surface analysis and the energy dispersed per surface contact area strategy to verify the testing conditions of both sub-scale and full scale testing. Since lab analysis costs are expensive, the project budget is restricted to analyzing the maximum of 1 full-scale disc and pad specimen and 2 subscale disc and pad sets. The test results are expected to prove that when the surface conditions of the analyzed specimens agree to each other, the dynamometer test results will also agree. Due to restrictions with budget and time the fastest and most effective way to test this hypothesis is by creating the baseline on the full-scale and then adjusting the scaling on the subscale dynamometer until similar results are given. Once similar dynamometer test results are obtained, the material specimens can be analyzed in the lab. Testing will continue as long as necessary, and if the expected results are not obtained, the results will still be tested for analysis and compared to the baseline. The results are expected to show that two separate machines may provide similar surface conditions for testing, as well as similar dynamometer test results for any given friction material. However, if the expected results cannot be obtained, then it may still prove that without matching the surface layer conditions while testing, the dynamometers recorded test results will not match either, which is in agreeance with the hypothesis.

Rock physical properties are usually associated with important geologic features within mineral deposits and can be used to define the location, depth and size of the deposit, type of ore, or physical property contrast between the host and country rock. Geophysical surveys are sensitive to physical properties and therefore are widely used in mining exploration, especially in concealed terrains. The surveys can be performed at multiple scales, resulting in corresponding physical property datasets at different scales. Survey scale can vary from core or hand sample, involving few cubic centimeters, to regional-scale surveys providing information about physical property contrasts between distinct regional geological features. The understanding of the relationship between the physical property distributions with the sample volume (e.g. district, deposit, and drill-hole scale) is required where point scale physical property measurements are going to be consistent with measurements at larger volumetric scales during the integration of data for geophysical modeling The approach used to address the problem of understanding the scaling relations of physical properties, was achieved by considering them as second order stationary regionalized variables and then applying the random function formalism, provided by geostatistics theory. Geostatistics provide the required framework to characterize, quantify, model and link the spatial variability of the random variable at the different volumetric scales. The aim of this study is to apply geostatistics to effectively integrate data collected at several scales and bring knowledge to the understanding of the scaling relations of magnetic susceptibility. For this purpose, measurements of magnetic susceptibility available from Flin Flon copper-zinc district in Canada will be used. The data available at point scale were collected with hand portable magnetic susceptibility meter. The larger volumetric scale dataset were acquired using frequency domain electromagnetic instruments capable of measuring larger sample volumes, and then used to obtain magnetic susceptibility models using geophysical inversion algorithms. Once different scale models of magnetic susceptibility were available, quantification of the scaling relation using geostatistics, specifically variogram models and dispersion variance were determined. The understanding provided by the scaling analysis of the Flin-Flon magnetic data is applied to data from the Rio Blanco copper district in central Chile. Magnetic susceptibility measurements collected with a hand magnetic susceptibility meter on drill-core is integrated in larger scale volumes used for geophysical inversion modeling of regional scale airborne magnetic field measurements to recover magnetic susceptibility models. The methodology resulting from this application of geostatistics is used to address the problem of integrating multiple scales of physical property data in an effective way. The resulting physical property models capture the small-scale magnetic susceptibility variability observed and can guide larger-scale variability within geophysical inversion models. Establishing reliable statistical correlations between physical properties and rock units controlling ore within deposits are crucial steps leading predictive mine exploration tools. Any numerical modeling approach to establish these correlations should consider in some way the scaling nature of both physical property and ore content. / Science, Faculty of / Earth, Ocean and Atmospheric Sciences, Department of / Graduate

A procedure for the design of a scaled aircraft using linear aeroelastic scaling is developed and demonstrated. Previous work has shown the viability in matching scaled structural frequencies and mode shapes in order to achieve consistent linear scaling of simple models. This methodology is adopted for use on a high fidelity joined-wing aircraft model. Natural frequencies and mode shapes are matched by optimizing structural ply properties and nonstructural mass. A full-scale SensorCraft concept developed by AFRL and Boeing serves as the target model, and a 1/9th span geometrically scaled remotely piloted vehicle (RPV) serves as the initial design point. The aeroelastic response of the final design is verified against the response of the full-scale model. Reasonable agreement is seen in both aeroelastic damping and frequency for a range of flight velocities, but some discrepancy remains in accurately capturing the flutter velocity. / Master of Science

Abstract Not Provided / Thesis / Master of Arts (MA)