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Decommissioning & Environmental Sciences
The mission of the Decommissioning and Environmental Sciences (DES) Division is to promote the development and use of those skills and technologies associated with the use of nuclear energy and the optimal management and stewardship of the environment, sustainable development, decommissioning, remediation, reutilization, and long-term surveillance and maintenance of nuclear-related installations, and sites. The target audience for this effort is the membership of the Division, the Society, and the public at large.
Meeting Spotlight
Conference on Nuclear Training and Education: A Biennial International Forum (CONTE 2025)
February 3–6, 2025
Amelia Island, FL|Omni Amelia Island Resort
Standards Program
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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Christmas Night
Twas the night before Christmas when all through the houseNo electrons were flowing through even my mouse.
All devices were plugged in by the chimney with careWith the hope that St. Nikola Tesla would share.
Satoshi Takeda, Takanori Kitada
Nuclear Science and Engineering | Volume 197 | Number 8 | August 2023 | Pages 1621-1633
Technical papers from: PHYSOR 2022 | doi.org/10.1080/00295639.2022.2123679
Articles are hosted by Taylor and Francis Online.
Assuming that the discrepancy between the experimental value and the calculation value comes from the cross section, experimental error, and calculation error, Bayesian estimation of the cross section and these errors were studied. Uncertainty of the discrepancy between the experimental value and the design value is discussed by comparing the present estimation and the bias factor method. Comparison of the formulas shows that the design value obtained by the bias factor method is consistent with that obtained by estimation of the cross section and calculation error of the target system. In addition, the uncertainty of the discrepancy between the experimental value and the design value can be reduced by considering a correlation of the experimental error between the mock-up experiment and the target system. A case study was performed using mixed oxide critical assembly benchmarks. The result shows that the experimental value of the target system can be accurately predicted by considering the cross section, experimental error, and calculation error.