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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.
Giovanni Maronati, Bojan Petrovic
Nuclear Technology | Volume 207 | Number 1 | January 2021 | Pages 1-18
Technical Paper | doi.org/10.1080/00295450.2020.1738829
Articles are hosted by Taylor and Francis Online.
Credibility requires predictability. Nuclear power plant (NPP) construction projects tend to be large and expensive, sometimes with high cost overruns far beyond those that might have been expected or predicted due to usual and recognized uncertainties and variations (e.g., in labor and materials costs combined with multiyear duration and complex construction logistics). This unaccounted for uncertainty brings the credibility of new NPP build projects into question and may prevent future projects from going forward. It is believed that the high initial capital cost of nuclear power is less of a hindering factor than the uncertainty about that cost. For nuclear power to regain credibility and enable future NPP construction projects, this unexpected uncertainty, or unknown unknown, needs to be assessed. Regular (expected) uncertainties (known unknowns) were addressed previously in a paper where the Iman-Conover method was used to account for correlated uncertainties. This paper addresses the impact of unexpected events (unknown unknowns), such as the Three Mile Island Unit 2 (TMI-2) accident. For this purpose, NPP construction in the United States is divided into two periods: pre-1979 (NPPs completed before the 1979 TMI-2 accident), and post-1979 (NPPs under construction when the accident happened and completed later). The latter group experienced significant schedule and budget overruns due to the change in regulation imposed after NPP construction was already under way. Analyzed a posteriori, this event and the escalated cost for the second group of NPPs was used to study the impact of a representative unexpected event.
An approach was developed to assess the range of potential risks, including those due to such unexpected events, and thus enable assigning appropriate contingencies. A traditional large four-loop pressurized water reactor [PWR12-Better Experience (BE)] was considered. With the inputs derived from the pre-1979 data, the expected total capital investment cost (TCIC) mean value for the PWR12-BE is found to be $3.3 billion, with a contingency of $1.3 billion, which corresponds to 39.4% of the TCIC mean. If the unknown unknowns are taken into account based on the post-1979 data, the TCIC mean value increases to $9.4 billion, with a cost contingency that is 108% of the TCIC mean derived for the pre-1979 NPPs.
Based on the experience-based assumed probability of unexpected events with large financial impact, it is then possible to derive an adequate contingency. The presented analysis offers a possible approach to treat unknown unknowns and to assess their impact on cost, providing the required contingency, as well as uncertainty in the construction time. In a broader context, this may provide quantitative tools to support making long-term energy policy decisions of new considered nuclear power projects.
