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Glass strategy: Hanford’s enhanced waste glass program
The mission of the Department of Energy’s Office of River Protection (ORP) is to complete the safe cleanup of waste resulting from decades of nuclear weapons development. One of the most technologically challenging responsibilities is the safe disposition of approximately 56 million gallons of radioactive waste historically stored in 177 tanks at the Hanford Site in Washington state.
ORP has a clear incentive to reduce the overall mission duration and cost. One pathway is to develop and deploy innovative technical solutions that can advance baseline flow sheets toward higher efficiency operations while reducing identified risks without compromising safety. Vitrification is the baseline process that will convert both high-level and low-level radioactive waste at Hanford into a stable glass waste form for long-term storage and disposal.
Although vitrification is a mature technology, there are key areas where technology can further reduce operational risks, advance baseline processes to maximize waste throughput, and provide the underpinning to enhance operational flexibility; all steps in reducing mission duration and cost.
Lubomír Bureš, Stefano Caruso
Nuclear Science and Engineering | Volume 191 | Number 1 | July 2018 | Pages 66-84
Technical Paper | doi.org/10.1080/00295639.2018.1442059
Articles are hosted by Taylor and Francis Online.
Knowledge of the radionuclide inventory in spent nuclear fuel is important for back-end operations such as fuel transport and storage, but it is also relevant for the postclosure safety case for a deep geological repository. Extensive depletion calculations using neutron transport solvers can be time consuming and resource intensive in the case of characterization of a large number of fuel assemblies. Issues of computational demand are further amplified when the inventory of only a single pin from the assembly is desired.
A new approach to speeding up the computational time without significant loss of accuracy is proposed in this work, consisting of simplification of the modeled geometry by means of stochastic optimization. The development of this novel methodology, the Acropolis methodology, is described in detail in this paper. Additionally, extensive benchmark and validation exercises were carried out to present and discuss the advantages and limitations of the proposed method.