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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.
R. R. Romatoski, L. W. Hu
Nuclear Technology | Volume 205 | Number 11 | November 2019 | Pages 1495-1512
Technical Paper | doi.org/10.1080/00295450.2019.1610686
Articles are hosted by Taylor and Francis Online.
An important fluoride-salt-cooled high-temperature reactor (FHR) development step is to design, build, and operate a test reactor. The uncertainties of the coolant thermophysical properties range between 2% and 20%. This study determines the effects of these high uncertainties by incorporating uncertainty propagation in a thermal-hydraulic safety analysis for test reactor licensing. A hot channel thermal-hydraulic model, Monte Carlo statistical sampling uncertainty propagation, and a limiting safety systems settings (LSSS) approach are combined to ensure sufficient margin to fuel and material thermal limits during steady-state operation while incorporating margin for high-uncertainty inputs. The method calculates LSSS parameters to define safe operation.
The methodology is applied to two test reactors currently considered, i.e., China’s first Solid Fueled Thorium Molten Salt Reactor (TMSR-SF1) pebble bed design and Massachusetts Institute of Technology’s Transportable FHR prismatic core design; two candidate coolants, i.e., flibe (LiF-BeF2) and nafzirf (NaF-ZrF4); and forced flow and natural circulation conditions to compare operating regions and LSSS power (maximum power not exceeding any thermal limits). The calculated operating region accounts for uncertainty (2σ) with an LSSS power for forced flows of 25.37 0.72, 22.56 1.15, 21.28 1.48, and 11.32 1.35 MW for pebble flibe, pebble nafzirf, prismatic flibe, and prismatic nafzirf, respectively. The pebble bed has superior heat transfer with an operating region reduced 10% less when switching coolants and 50% smaller uncertainty than the prismatic. The maximum fuel temperature constrains the pebble bed while the maximum coolant temperature constrains the prismatic due to different dominant heat transfer modes. Sensitivity analysis revealed that (1) thermal conductivity and thus conductive heat transfer dominate in the prismatic design while convection is superior in the pebble bed and (2) the impact of thermophysical property uncertainties is ranked and should be considered for experimental measurements in the following order: thermal conductivity, heat capacity, density, and last, viscosity. Broadly, the methodology incorporates uncertainty propagation that can be used to evaluate parametric uncertainties to satisfy guidelines for nonpower reactor licensing applications, and its application shows that the pebble bed is more attractive for thermal-hydraulic safety. Although the method is developed and evaluated for coolant property uncertainties, it is readily applicable for other parameters of interest.