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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.
Deokjung Lee, Thomas J. Downar, Yonghee Kim
Nuclear Science and Engineering | Volume 147 | Number 2 | June 2004 | Pages 127-147
Technical Paper | doi.org/10.13182/NSE03-64
Articles are hosted by Taylor and Francis Online.
The convergence rates of the nonlinear coarse-mesh finite difference (CMFD) method and the coarse-mesh rebalance (CMR) method are derived analytically for one-dimensional, one-group solutions of the fixed-source diffusion problem in a nonmultiplying infinite homogeneous medium. The derivation was performed by linearizing the nonlinear algorithm and by applying Fourier error analysis to the linearized algorithm. The mesh size measured in units of the diffusion length is shown to be a dominant parameter for the convergence rate and for the stability of the iterative algorithms. For a small mesh size problem, the nonlinear CMFD is shown to be a more effective acceleration method than CMR. Both CMR and two-node CMFD algorithms are shown to be unconditionally stable. However, the one-node CMFD becomes unstable for large mesh sizes. To remedy this instability, an underrelaxation of the current correction factor for the one-node CMFD method is successfully introduced, and the domain of stability is significantly expanded. Furthermore, the optimum underrelaxation parameter is analytically derived, and the one-node CMFD with the optimum relaxation is shown to be unconditionally stable.