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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.
Siying Dong, Wei Liu, Yang Liu, Jianqiang Shan
Nuclear Technology | Volume 205 | Number 1 | January-February 2019 | Pages 352-363
Technical Paper | doi.org/10.1080/00295450.2018.1491182
Articles are hosted by Taylor and Francis Online.
In most subchannel analysis codes, spacer grids are simulated using an effective loss coefficient that can account only for the spacer grid’s mean axial effect on the pressure drop. Since the mixing vane spacer grid (MVG) in a rod bundle has great influence on local flow fields, neglecting the effect of mixing vanes will degrade fidelity and resolution in thermal-hydraulic calculation. This paper focuses on improving the spacer grid model in subchannel analysis. First, cross-flow mixing effects of MVGs are accounted for by applying the distributed resistance method. By choosing resistance correlation appropriately and considering the geometric dimensions of mixing vanes, the source term of mixing vanes can be represented quantitatively in the axial and lateral momentum equations of a subchannel analysis code. Second, the Carlucci model is used to calculate mixing rates, and obstruction factor Fobs is introduced to consider turbulent mixing effects caused by spacer grids. The improved MVG cross-flow model and turbulent mixing model are implemented in the subchannel code ATHAS. Validation is provided for the 5 × 5 rod bundle experiments provided by Karoutas et al. [Proc. 7th Int. Mtg. Nuclear Reactor Thermal-Hydraulics (NURETH-7), Saratoga, New York (1995)] and high-quality experimental data provided by the Organisation for Economic Co-operation and Development/U.S. Nuclear Regulatory Commission Pressurized Water Reactor Subchannel and Bundle Test (PSBT) benchmark to demonstrate their effects and accuracy. From the validation, it can be concluded that the calculated lateral velocities agree well with those provided by the experimental data. In addition, the improved cross-flow and turbulent mixing models significantly increase the accuracy of predictions of exit subchannel coolant temperatures, with reduction in root-mean-square error to be 2.27 K.