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GAO: Clarification of HLW definition could save DOE billions
A clearer definition of what constitutes high-level radioactive waste could save the Department of Energy’s Office of Environmental Management “tens of billions of dollars” in waste management costs and accelerate its cleanup schedule by decades, according to a report by the U.S. Government Accountability Office.
DOE-EM’s efforts to manage waste resulting from legacy spent nuclear fuel reprocessing have been hindered for decades by the ambiguity of the statutory definition of HLW as laid out in the Atomic Energy Act and Nuclear Waste Policy Act, the report states. While admitting that the DOE has taken steps to overcome this ambiguity, the GAO says that the department has not fully evaluated all available opportunities to treat and dispose of waste more economically as either transuranic or low-level radioactive waste.
Paul M. Keller, Paul J. Turinsky
Nuclear Science and Engineering | Volume 139 | Number 3 | November 2001 | Pages 235-247
Technical Paper | doi.org/10.13182/NSE01-A2234
Articles are hosted by Taylor and Francis Online.
A methodology has been developed whereby a three-dimensional (3-D) geometry, nodal expansion method (NEM), pressurized water reactor (PWR) core simulator model is collapsed to form an equivalent two-dimensional (2-D) geometry model that preserves approximately, but with negligible loss of fidelity, the global quantities and axially integrated reaction rates and surface currents of the 3-D model. In comparison with typical licensed-quality 3-D models, the 2-D collapsed NEM model typically requires a factor of 50 less computational time and exhibits root-mean-square (rms) assembly relative power fraction errors, as compared with the original 3-D model, of 5 × 10-3 over an entire fuel cycle, and average maximum errors over the fuel cycle of 1 × 10-2. The collapse methodology includes a pin reconstruction methodology, which exhibits assemblywise rms pin power errors of 5 × 10-3 and average maximum assemblywise pin power errors of 1.2 × 10-2. When coupled with FORMOSA-P's existing assembly power response generalized perturbation theory reactor core simulator, this permits loading-pattern evaluations at a speed approximately 100 to 150 times faster than full, 3-D models, providing the computational efficiency needed for efficient incore fuel management optimization using stochastic methods.