Waste Classification based on Waste Form Heat Generation in Advanced Nuclear Fuel Cycles Using the Fuel-Cycle Integration and Tradeoffs (FIT) Model - 13413
- Department of Nuclear Engineering, University of California - Berkeley, 4149 Etcheverry Hall, Berkeley, CA 94720-1730 (United States)
- Idaho National Laboratory - INL, 2525 North Fremont Avenue, Idaho Falls, ID 83415 (United States)
This study explores the impact of wastes generated from potential future fuel cycles and the issues presented by classifying these under current classification criteria, and discusses the possibility of a comprehensive and consistent characteristics-based classification framework based on new waste streams created from advanced fuel cycles. A static mass flow model, Fuel-Cycle Integration and Tradeoffs (FIT), was used to calculate the composition of waste streams resulting from different nuclear fuel cycle choices. This analysis focuses on the impact of waste form heat load on waste classification practices, although classifying by metrics of radiotoxicity, mass, and volume is also possible. The value of separation of heat-generating fission products and actinides in different fuel cycles is discussed. It was shown that the benefits of reducing the short-term fission-product heat load of waste destined for geologic disposal are neglected under the current source-based radioactive waste classification system, and that it is useful to classify waste streams based on how favorable the impact of interim storage is in increasing repository capacity. (authors)
- Research Organization:
- WM Symposia, 1628 E. Southern Avenue, Suite 9-332, Tempe, AZ 85282 (United States)
- OSTI ID:
- 22221387
- Report Number(s):
- INIS-US-13-WM-13413; TRN: US14V0581042342
- Resource Relation:
- Conference: Waste Management 2013 - WM2013 Conference: International collaboration and continuous improvement, Phoenix, AZ (United States), 24-28 Feb 2013; Other Information: Country of input: France; 7 refs.
- Country of Publication:
- United States
- Language:
- English
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