ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
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Division Spotlight
Robotics & Remote Systems
The Mission of the Robotics and Remote Systems Division is to promote the development and application of immersive simulation, robotics, and remote systems for hazardous environments for the purpose of reducing hazardous exposure to individuals, reducing environmental hazards and reducing the cost of performing work.
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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Nuclear Science and Engineering
February 2025
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Latest News
IAEA’s nuclear security center offers hands-on training
In the past year and a half, the International Atomic Energy Agency has established the Nuclear Security Training and Demonstration Center (NSTDC) to help countries strengthen their nuclear security regimes. The center, located at the IAEA’s Seibersdorf laboratories outside Vienna, Austria, has been operational since October 2023.
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.