2026-09-18T20:28:52Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/627042026-06-06T01:06:25Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Michael Driscoll.
Matthews, Isaac A
Massachusetts Institute of Technology. Technology and Policy Program.
Massachusetts Institute of Technology. Department of Nuclear Science and Engineering
Massachusetts Institute of Technology. Engineering Systems Division
Technology and Policy Program
2011-05-09T15:22:41Z
2011-05-09T15:22:41Z
2010
2010
http://hdl.handle.net/1721.1/62704
714604967
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Nuclear Science and Engineering; and, (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 99-104).
An accurate outlook on long-term uranium resources is critical in forecasting uranium costresource relationships, and for energy policy planning as regards the development and deployment of nuclear fuel cycle alternatives. In this study, which was part of the MIT Study on the Future of the Nuclear Fuel Cycle, uranium production cost projections over the next half-century are enabled through the development of a comprehensive model for resource cost ($/kg of U30 8) versus cumulative energy generation (GWe-yr). The probabilistic cost model incorporates three sub-models including Deffeyes' crustal abundance model, learning/experience effects, and economies/diseconomies of scale. Using Monte Carlo techniques to develop a cdf of the resource cost correlation factor (0), in the expression ($ 1kg) a (GWe yruiativ,, the resulting model encompasses three probabilistic industry growth scenarios, pessimistic, prudent, and optimistic, representative of confidence levels of s 85%, s 50%, and s 15%, respectively. The impacts of current domestic and international nuclear policies on industry growth (and subsequently uranium market pricing) are also evaluated, considering waste management, uranium stockpiling, and proliferation. Moreover, various options to optimize natural uranium usage including the reduction of tails during the enrichment phase, recycling reenriched uranium from SNF, recycling TRU in LWRs, and optimizing fuel burn-up are presented. Further insight is provided to examine the energy balance and environmental impacts of once-through fuel cycles as compared to recycling/ reprocessing options and other nuclear and non-nuclear fuel-cycle alternatives. The economic viability of SNF recycling and reprocessing, deployment of breeder reactors, and use of unconventional resources including thorium and seawater uranium are discussed in the conclusions of this study. The results of the study confirm that once-through LWR fuel cycles can sustain aggressive expansion of nuclear power and can remain competitive well beyond the mid-century mark; however, volatility of uranium spot prices is expected until uranium resource production/consumption equilibrium is reached.
by Isaac A. Matthews.
S.M. in Technology and Policy
S.M.
142 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
copyright. They may be viewed from this source for any purpose, but
reproduction or distribution in any format is prohibited without written
permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Nuclear Science and Engineering.
Engineering Systems Division.
Technology and Policy Program.
Global terrestrial uranium supply and its policy implications : a probabilistic projection of future uranium costs
Thesis
application/pdf
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Publication
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<Abstract>An accurate outlook on long-term uranium resources is critical in forecasting uranium costresource relationships, and for energy policy planning as regards the development and deployment of nuclear fuel cycle alternatives. In this study, which was part of the MIT Study on the Future of the Nuclear Fuel Cycle, uranium production cost projections over the next half-century are enabled through the development of a comprehensive model for resource cost ($/kg of U30 8) versus cumulative energy generation (GWe-yr). The probabilistic cost model incorporates three sub-models including Deffeyes' crustal abundance model, learning/experience effects, and economies/diseconomies of scale. Using Monte Carlo techniques to develop a cdf of the resource cost correlation factor (0), in the expression ($ 1kg) a (GWe yruiativ,, the resulting model encompasses three probabilistic industry growth scenarios, pessimistic, prudent, and optimistic, representative of confidence levels of s 85%, s 50%, and s 15%, respectively. The impacts of current domestic and international nuclear policies on industry growth (and subsequently uranium market pricing) are also evaluated, considering waste management, uranium stockpiling, and proliferation. Moreover, various options to optimize natural uranium usage including the reduction of tails during the enrichment phase, recycling reenriched uranium from SNF, recycling TRU in LWRs, and optimizing fuel burn-up are presented. Further insight is provided to examine the energy balance and environmental impacts of once-through fuel cycles as compared to recycling/ reprocessing options and other nuclear and non-nuclear fuel-cycle alternatives. The economic viability of SNF recycling and reprocessing, deployment of breeder reactors, and use of unconventional resources including thorium and seawater uranium are discussed in the conclusions of this study. The results of the study confirm that once-through LWR fuel cycles can sustain aggressive expansion of nuclear power and can remain competitive well beyond the mid-century mark; however, volatility of uranium spot prices is expected until uranium resource production/consumption equilibrium is reached.</Abstract>
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