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ANS Student Conference 2025
April 3–5, 2025
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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.
Yanzi Liu, Xuegang Zhang, Gang Zhang, Jianjun Jiang, Li Zhang, Hong Hu, Tao Qing, Yanhua Zou, Dan Yang, Liaozi Xi, Fan Tang, Ming Jia, Yiqian Wu, Zhiyao Liu
Nuclear Technology | Volume 207 | Number 1 | January 2021 | Pages 74-93
Technical Paper | doi.org/10.1080/00295450.2020.1733376
Articles are hosted by Taylor and Francis Online.
The digital control system (DCS)+state-oriented procedure (SOP) system adopted by China’s Ling’ao Phase II nuclear power plant’s main control room requires changes to the cognitive process, behavior mode, and error mode while triggering new human factors. Therefore, in this paper we present a cognitive reliability model for the DCS+SOP system in the Ling’ao Phase II Nuclear Power Plant’s main control room and conduct a human reliability analysis. The model is based on the cognitive process with respect to considering the coordinator’s accident recovery effect and obtaining the method of calculating cognitive reliability. We determine impact factors for the three cognitive stages of the operator’s and the coordinator’s diagnosis, decision making, and operation. We obtain the operator’s and the coordinator’s weights for each process through an analytic hierarchy process. Using methods of simulation and analyzing the experiment data, we obtain revised coefficients for the cognitive reliability model. Additionally, the trend of the simulation curve indicates the rationality of the model. Finally, we provide an example based on the proposed cognitive reliability model. The process of analyzing the example demonstrates that this method provides a feasible analysis method for the cognitive reliability of the DCS+SOP system in the main control room.