A family of top-down statistical models describing energy consumption in the mining, milling, and refining of uranium are formulated. The purpose of the models is to estimate the energy-to-grade dependence for uranium extraction, while defining a minimum grade that can be feasibly mined and produced. The results serve as a basis for understanding the factors governing energy consumption in the production of U3O8. The models are applied to a considerably larger data set of operating mines than in any previous effort. In addition, the validity of the modeling approach is established by modeling energy for two other commodities, gold and copper, thereby showing it can be applied to other metals.
Statistical measures of explanatory power show that the models the energy-to-grade relationship is well-described for both uranium and gold. For
copper, there was insufficient data over a broad range of ore grades to obtain a model that passed statistical confidence measures. The results show that mining of lower-grade deposits of uranium is likely to be less energy-intensive than previous investigators concluded. It is shown that the uncertainty in the results is dominated by the contribution of the grade-independent component of energy consumption. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/ETD-UT-2010-12-2286 |
| Date | 16 February 2011 |
| Creators | Tavrides, Emily Loree |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Type | thesis |
| Format | application/pdf |
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