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Division Spotlight
Fuel Cycle & Waste Management
Devoted to all aspects of the nuclear fuel cycle including waste management, worldwide. Division specific areas of interest and involvement include uranium conversion and enrichment; fuel fabrication, management (in-core and ex-core) and recycle; transportation; safeguards; high-level, low-level and mixed waste management and disposal; public policy and program management; decontamination and decommissioning environmental restoration; and excess weapons materials disposition.
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2023 ANS Annual Meeting
June 11–14, 2023
Indianapolis, IN|Marriott Indianapolis Downtown
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The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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The Civil Nuclear Credit Program: An overview
Officially established on November 15, 2021, with the signing of the $1.2 trillion Infrastructure Investment and Jobs Act—aka the Bipartisan Infrastructure Law, or BIL—the Department of Energy’s Civil Nuclear Credit Program was designed to give owners/operators of commercial U.S. reactors the opportunity to apply for certification and competitively bid on credits to help support the continued operation of economically troubled units. Finally, the federal government, and not just certain farsighted state governments, would recognize nuclear energy for its important grid reliability and decarbonization attributes.
J. Barhen, D. G. Cacuci, J. J. Wagschal, M. A. Bjerke, C. B. Mullins
Nuclear Science and Engineering | Volume 81 | Number 1 | May 1982 | Pages 23-44
Technical Paper | doi.org/10.13182/NSE82-3
Articles are hosted by Taylor and Francis Online.
An advanced methodology for performing systematic uncertainty analysis of time-dependent nonlinear systems is presented. This methodology includes a capability for reducing uncertainties in system parameters and responses by using Bayesian inference techniques to consistently combine prior knowledge with additional experimental information. The determination of best estimates for the system parameters, for the responses, and for their respective covariances is treated as a time-dependent constrained minimization problem. Three alternative formalisms for solving this problem are developed. The two “off-line” formalisms, with and without “foresight” characteristics, require the generation of a complete sensitivity data base prior to performing the uncertainty analysis. The “online” formalism, in which uncertainty analysis is performed interactively with the system analysis code, is best suited for treatment of large-scale highly nonlinear time-dependent problems. This methodology is applied to the uncertainty analysis of a transient upflow of a high pressure water heat transfer experiment. For comparison, an uncertainty analysis using sensitivities computed by standard response surface techniques is also performed. The results of the analysis indicate the following. 1. Major reduction of the discrepancies in the calculation/experiment ratios is achieved by using the new methodology. 2. Incorporation of in-bundle measurements in the uncertainty analysis significantly reduces system uncertainties. 3. Accuracy of sensitivities generated by response-surface techniques should be carefully assessed prior to using them as a basis for uncertainty analyses of transient reactor safety problems. Conclusions about the future applicability of the uncertainty analysis methodology presented in this work are also discussed.