Modeling of Glass Making Processes for Improved Efficiency | |
III, Thomas P. Seward | |
NYSCC, Alfred University, Alfred, NY (United States) | |
关键词: Glass Industry; Gas Solubility; Information Systems; Resistivity; Glass; | |
DOI : 10.2172/809193 RP-ID : DOE/EE41262-2 RP-ID : FG07-96EE41262 RP-ID : 809193 |
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美国|英语 | |
来源: UNT Digital Library | |
【 摘 要 】
The overall goal of this project was to develop a high-temperature melt properties database with sufficient reliability to allow mathematical modeling of glass melting and forming processes for improved product quality, improved efficiency and lessened environmental impact. It was initiated by the United States glass industry through the NSF Industry/University Center for Glass Research (CGR) at Alfred University [1]. Because of their important commercial value, six different types/families of glass were studied: container, float, fiberglass (E- and wool-types), low-expansion borosilicate, and color TV panel glasses. CGR member companies supplied production-quality glass from all six families upon which we measured, as a function of temperature in the molten state, density, surface tension, viscosity, electrical resistivity, infrared transmittance (to determine high temperature radiative conductivity), non-Newtonian flow behavior, and oxygen partial pres sure. With CGR cost sharing, we also studied gas solubility and diffusivity in each of these glasses. Because knowledge of the compositional dependencies of melt viscosity and electrical resistivity are extremely important for glass melting furnace design and operation, these properties were studied more fully. Composition variations were statistically designed for all six types/families of glass. About 140 different glasses were then melted on a laboratory scale and their viscosity and electrical resistivity measured as a function of temperature. The measurements were completed in February 2003 and are reported on here. The next steps will be (1) to statistically analyze the compositional dependencies of viscosity and electrical resistivity and develop composition-property response surfaces, (2) submit all the data to CGR member companies to evaluate the usefulness in their models, and (3) publish the results in technical journals and most likely in book form.
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809193.pdf | 671KB | download |