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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.
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2021 Student Conference
April 8–10, 2021
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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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February 2021
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Fusion Science and Technology
November 2020
Latest News
Understanding the ITER Project in the context of global Progress on Fusion
(photo: ITER Project gangway assembly)
The promise of hydrogen fusion as a safe, environmentally friendly, and virtually unlimited source of energy has motivated scientists and engineers for decades. For the general public, the pace of fusion research and development may at times appear to be slow. But for those on the inside, who understand both the technological challenges involved and the transformative impact that fusion can bring to human society in terms of the security of the long-term world energy supply, the extended investment is well worth it.
Failure is not an option.
Taro Ueki
Nuclear Science and Engineering | Volume 194 | Number 6 | June 2020 | Pages 422-432
Technical Paper | dx.doi.org/10.1080/00295639.2019.1710418
Articles are hosted by Taylor and Francis Online.
In the Monte Carlo method for criticality calculation, the convergence-in-distribution check of the sample mean of tallies can be approached in terms of the influence range of autocorrelation compared to the total number of generations iterated. In this context, it is necessary to evaluate the attenuation of autocorrelation coefficients (ACCs) over lags. However, in just one replica of calculation, it is difficult to accurately estimate small ACCs at large lags because of the comparability with statistical uncertainty. This paper proposes a method to overcome such an issue. Its essential component is the transformation of a standardized time series of tallies so that the resulting series asymptotically converges in distribution to Brownian motion. The convergence-in-distribution check is then constructed based on the independent increment property of Brownian motion. The judgment criterion is set by way of the spectral analysis of fractional Brownian motion. Numerical results are demonstrated for extreme and standard types of criticality calculation and different numbers of histories per generation. Excellent performance is observed for most replicas of calculation. An issue related to small numbers of generations is addressed for strongly autocorrelated tallies in the extreme type.