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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.
L. Eric Smith, Naeem M. Abdurrahman
Nuclear Technology | Volume 140 | Number 3 | December 2002 | Pages 328-349
Technical Paper | Radiation Measurements and Instrumentation | doi.org/10.13182/NT02-A3343
Articles are hosted by Taylor and Francis Online.
A Monte Carlo study of the neutron slowing-down spectrometry technique for measuring fissile isotopic content in irradiated fuel has been completed. The neutron spectrometer system is characterized in terms of design, slowing-down time relation, isotopic response functions, and assay signals. The nonlinear effect of interrogating neutron self-shielding for a high fissile content fuel is compared to the same parameter for a low fissile content fuel. Simulated assays of 23 different fuel assemblies with a broad range of total fissile mass content (1.3 to 83 wt%) and fissile isotopic ratios are performed and analyzed using two different methods: a linear system model using a least-squares regression analysis and a radial basis neural network. Mean errors using the linear system model for the 23 different fuel types were approximately 20% for 235U and 43% for total plutonium. The radial basis neural network assay signal solutions showed promising results, considerably better than the linear model: 4.9% for 235U, 5.4% for total plutonium, and 0.5% for total fissile content.
