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Decommissioning & Environmental Sciences
The mission of the Decommissioning and Environmental Sciences (DES) Division is to promote the development and use of those skills and technologies associated with the use of nuclear energy and the optimal management and stewardship of the environment, sustainable development, decommissioning, remediation, reutilization, and long-term surveillance and maintenance of nuclear-related installations, and sites. The target audience for this effort is the membership of the Division, the Society, and the public at large.
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Norway’s Halden reactor takes first step toward decommissioning
The government of Norway has granted the transfer of the Halden research reactor from the Institute for Energy Technology (IFE) to the state agency Norwegian Nuclear Decommissioning (NND). The 25-MWt Halden boiling water reactor operated from 1958 to 2018 and was used in the research of nuclear fuel, reactor internals, plant procedures and monitoring, and human factors.
D. R. Reinert, E. A. Schneider, S. R. F. Biegalski
Nuclear Science and Engineering | Volume 166 | Number 2 | October 2010 | Pages 167-174
Technical Paper | doi.org/10.13182/NSE09-45
Articles are hosted by Taylor and Francis Online.
This paper reviews existing Monte Carlo techniques for performing neutron transport simulations in binary random heterogeneous fissile fuels and presents a new approach offering superior efficiency at little cost in fidelity for problems involving densely packed, optically thick absorbers. The accuracy of the chord-length sampling technique is demonstrated to be a function of the total optical thicknesses and optical scattering thickness of the constituent materials as well as the packing density of the fissile kernels. The results of this parameter assessment provide a foundation for an original hybrid algorithm that combines homogeneous and explicit geometry models within a single Monte Carlo simulation. The geometry model utilized is selected according to the energy-dependent optical thickness. By partitioning the geometry representation within a single Monte Carlo simulation into homogenous and heterogeneous energy-dependent models, acceptable ensemble average results are obtained in a fraction of the run time of the detailed explicit geometry benchmark method.