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DNFSB spots possible bottleneck in Hanford’s waste vitrification
Workers change out spent 27,000-pound TSCR filter columns and place them on a nearby storage pad during a planned outage in 2023. (Photo: DOE)
While the Department of Energy recently celebrated the beginning of hot commissioning of the Hanford Site’s Waste Treatment and Immobilization Plant (WTP), which has begun immobilizing the site’s radioactive tank waste in glass through vitrification, the Defense Nuclear Facilities Safety Board has reported a possible bottleneck in waste processing. According to the DNFSB, unless current systems run efficiently, the issue could result in the interruption of operations at the WTP’s Low-Activity Waste Facility, where waste vitrification takes place.
During operations, the LAW Facility will process an average of 5,300 gallons of tank waste per day, according to Bechtel, the contractor leading design, construction, and commissioning of the WTP. That waste is piped to the facility after being treated by Hanford’s Tanks Side Cesium Removal (TSCR) system, which filters undissolved solid material and removes cesium from liquid waste.
According to a November 7 activity report by the DNFSB, the TSCR system may not be able to produce waste feed fast enough to keep up with the LAW Facility’s vitrification rate.
A. Kemal Ziver, Jonathan N. Carter, Christopher C. Pain, Cassiano R. E. de Oliveira, Antony J. H. Goddard, Richard S. Overton
Nuclear Technology | Volume 141 | Number 2 | February 2003 | Pages 122-141
Technical Paper | Fuel Cycle and Management | doi.org/10.13182/NT03-A3355
Articles are hosted by Taylor and Francis Online.
A genetic algorithm (GA)-based optimizer (GAOPT) has been developed for in-core fuel management of advanced gas-cooled reactors (AGRs) at HINKLEY B and HARTLEPOOL, which employ on-load and off-load refueling, respectively. The optimizer has been linked to the reactor analysis code PANTHER for the automated evaluation of loading patterns in a two-dimensional geometry, which is collapsed from the three-dimensional reactor model. GAOPT uses a directed stochastic (Monte Carlo) algorithm to generate initial population members, within predetermined constraints, for use in GAs, which apply the standard genetic operators: selection by tournament, crossover, and mutation. The GAOPT is able to generate and optimize loading patterns for successive reactor cycles (multicycle) within acceptable CPU times even on single-processor systems. The algorithm allows radial shuffling of fuel assemblies in a multicycle refueling optimization, which is constructed to aid long-term core management planning decisions. This paper presents the application of the GA-based optimization to two AGR stations, which apply different in-core management operational rules. Results obtained from the testing of GAOPT are discussed.
