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DOE launches UPRISE to boost nuclear capacity
The Department of Energy’s Office of Nuclear Energy has launched a new initiative to meet the government’s goal of increasing U.S. nuclear energy capacity by boosting the power output of existing nuclear reactors through uprates and restarts and by completing stalled reactor projects.
UPRISE, the Utility Power Reactor Incremental Scaling Effort, managed by Idaho National Laboratory, is to “deliver immediate results that will accelerate nuclear power growth and foster innovation to address the nation’s urgent energy needs,” DOE-NE said in its announcement.
W. Haeck, B. Verboomen
Nuclear Science and Engineering | Volume 156 | Number 2 | June 2007 | Pages 180-196
Technical Paper | doi.org/10.13182/NSE07-A2695
Articles are hosted by Taylor and Francis Online.
Monte Carlo codes are powerful and accurate tools for reactor core calculations. For coupled core-evolution applications, however, they remain rather demanding on calculation time because of the sheer number of reaction rates required for the evolution calculation. To make Monte Carlo burnup codes more efficient, we must therefore optimize reaction rate calculation to reduce calculation time without loss of accuracy. In the optimal situation, the calculation time of the Monte Carlo burnup code should be as close as possible to that of the basic Monte Carlo simulation. Through a deep analysis of the Monte Carlo simulation process as implemented in MCNP or MCNPX, we have developed an optimum approach called hereafter the multigroup binning approach to reaction rate calculation. In this paper, we have analyzed the performance of the multigroup binning approach as compared to a generic Monte Carlo burnup code. We have implemented this multigroup binning approach into ALEPH, a C++ interface code coupling MCNP or MCNPX, and ORIGEN. A number of validation benchmarks and applications of ALEPH to particular problems such as the rim effect and the High Flux Isotope Reactor of Oak Ridge National Laboratory have also been presented.