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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.
S. Schwarz, K. Fischer, A. Bentaib, J. Burkhardt, J.-J. Lee, J. Duspiva, D. Visser, J. Kyttälä, P. Royl, J. Kim, P. Kostka, R. Liang
Nuclear Technology | Volume 175 | Number 3 | September 2011 | Pages 594-603
Technical Paper | NURETH-13 Special / Reactor Safety | doi.org/10.13182/NT11-A12508
Articles are hosted by Taylor and Francis Online.
Within the course of a hypothetical severe accident in a nuclear power plant, hydrogen can be generated in the primary circuit and released into the containment. Considering the possibility of a deflagration, the simulation of the hydrogen distribution in the containment by computer codes is of major importance. To create a database for code validation, several distribution experiments using helium and hydrogen have been performed in the German Thermal Hydraulics, Hydrogen, Aerosols, Iodine (THAI) facility. The experiments started with the TH13 test, which was the base of the International Standard Problem exercise (ISP-47). TH13 was followed by the Hydrogen-Helium Material Scaling (HM) test series conducted within the Organisation for Economic Co-operation and Development/Nuclear Energy Agency (OECD/NEA) THAI project. The objectives of the HM tests were (a) to confirm the transferability of existing helium distribution test data to hydrogen distribution problems and (b) to understand the processes that lead to the formation and dissolution of a light gas cloud stratification. The HM-2 test was chosen for a code benchmark.During the first phase of the HM-2 test, a light gas cloud consisting of hydrogen and nitrogen was established in the upper half of the facility. In the second phase, steam was injected at a lower position inducing a rising steam-nitrogen plume. The plume did not break through the cloud because its density was higher than the density of the cloud. Therefore, the cloud was gradually dissolved from its bottom.Eleven organizations performed blind calculations for the HM-2 experiment. The lumped parameter (LP) codes ASTEC, COCOSYS, and MELCOR and the computational fluid dynamics (CFD) codes FLUENT, GASFLOW, and GOTHIC were used. The main phenomena were natural convection, interaction between the rising plume and the light gas cloud, steam condensation on walls, fog behavior, and heat up of the walls. The experimental data of the first phase were published, and the atmospheric stratification was simulated reasonably well. The data from the second phase stayed concealed until the simulated results were submitted. The thermal-hydraulic phenomena were well predicted by several LP and CFD contributions, whereas the time intervals needed to dissolve the light gas cloud were either underpredicted or overpredicted. However, the other LP and CFD contributions showed larger deviations in the measured data. Reasons for deviations were identified, and model improvements were demonstrated in open posttest calculations. In this article, the experiment, the benchmark results, and the simulation features are described, and recommendations for code users are given.