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High-temperature plumbing and advanced reactors
The use of nuclear fission power and its role in impacting climate change is hotly debated. Fission advocates argue that short-term solutions would involve the rapid deployment of Gen III+ nuclear reactors, like Vogtle-3 and -4, while long-term climate change impact would rely on the creation and implementation of Gen IV reactors, “inherently safe” reactors that use passive laws of physics and chemistry rather than active controls such as valves and pumps to operate safely. While Gen IV reactors vary in many ways, one thing unites nearly all of them: the use of exotic, high-temperature coolants. These fluids, like molten salts and liquid metals, can enable reactor engineers to design much safer nuclear reactors—ultimately because the boiling point of each fluid is extremely high. Fluids that remain liquid over large temperature ranges can provide good heat transfer through many demanding conditions, all with minimal pressurization. Although the most apparent use for these fluids is advanced fission power, they have the potential to be applied to other power generation sources such as fusion, thermal storage, solar, or high-temperature process heat.1–3
Anthony M. Scopatz, Erich A. Schneider, Jun Li, Man-Sung Yim
Nuclear Technology | Volume 183 | Number 1 | July 2013 | Pages 45-61
Technical Paper | Fuel Cycle and Management | doi.org/10.13182/NT13-A16991
Articles are hosted by Taylor and Francis Online.
Technology development and deployment decisions are justified by weighing their costs against the expected benefits. Multiple nuclear fuel cycle (NFC) simulation models have been devised, some with the aim of quantifying cyclewide sensitivities to variations from base-case scenarios. Base-case sensitivity studies often perturb only one parameter at a time and only in the region around the initial value. This paper details a sensitivity study methodology that applies entropy-based statistical methods of information theory to describe outcomes produced by an NFC model. This supersedes past efforts at sensitivity and uncertainty analysis by allowing a much larger space to be explored. Here, 30 independent fuel cycle parameters for a fast reactor-light water reactor hybrid scenario are varied simultaneously and stochastically. This fuel cycle schema was chosen as a well-known, sufficiently complex model; the underlying statistical methods could be applied to any cycle. This study uses the uncertainty coefficient computed from contingency tables (CTs) to represent the sensitivity of a technology-defining input to the response. The response of interest here was taken to be the deep geologic repository capacity for a given realization of fuel cycle inputs. After computing the uncertainty coefficients, the inputs themselves are sorted based on decreasing sensitivities. Fast reactor used fuel plutonium separations were found to be most important to the cycle. Furthermore, to represent input covariances (the effect of one input on the sensitivity of a second input to the response), a new measure is defined on three-dimensional CTs. This metric is the coefficient of the variation of uncertainty coefficient of two-dimensional slices of the original table. Sorting by this sensitivity of sensitivity metric, the input pair of fast reactor americium separations together with high-level-waste storage time was found to have the largest joint effect on the repository capacity.