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Colin Judge: Testing structural materials in Idaho’s newest hot cell facility
Idaho National Laboratory’s newest facility—the Sample Preparation Laboratory (SPL)—sits across the road from the Hot Fuel Examination Facility (HFEF), which started operating in 1975. SPL will host the first new hot cells at INL’s Materials and Fuels Complex (MFC) in 50 years, giving INL researchers and partners new flexibility to test the structural properties of irradiated materials fresh from the Advanced Test Reactor (ATR) or from a partner’s facility.
Materials meant to withstand extreme conditions in fission or fusion power plants must be tested under similar conditions and pushed past their breaking points so performance and limitations can be understood and improved. Once irradiated, materials samples can be cut down to size in SPL and packaged for testing in other facilities at INL or other national laboratories, commercial labs, or universities. But they can also be subjected to extreme thermal or corrosive conditions and mechanical testing right in SPL, explains Colin Judge, who, as INL’s division director for nuclear materials performance, oversees SPL and other facilities at the MFC.
SPL won’t go “hot” until January 2026, but Judge spoke with NN staff writer Susan Gallier about its capabilities as his team was moving instruments into the new facility.
Cecilia Martin-del-Campo, Juan Luis François, Alejandra M. Barragan, Miguel A. Palomera
Nuclear Technology | Volume 157 | Number 3 | March 2007 | Pages 251-260
Technical Paper | Fuel Cycle and Management | doi.org/10.13182/NT07-A3816
Articles are hosted by Taylor and Francis Online.
Construction of a fuzzy inference system for describing the objective function in a fuel lattice composition optimization problem is proposed. This technique allows for incorporating human expertise in searching for the best radial fuel enrichment and gadolinia distributions in a typical boiling water reactor fuel lattice. The optimization procedure adopted is a modified tabu search algorithm. Evaluation parameters included in the objective function are obtained by the neutronic lattice simulator HELIOS. The performance of the new objective function is compared to the objective function consisting in a single sum of individual objectives pondered by weighting factors. Results show that the fuzzy inference system performs very well for modeling the objective function in order to qualify the investigated solutions in a fuel composition lattice optimization process based on tabu search. The best solution found is a lattice with the desired neutronic characteristic.
