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Fusion Energy
This division promotes the development and timely introduction of fusion energy as a sustainable energy source with favorable economic, environmental, and safety attributes. The division cooperates with other organizations on common issues of multidisciplinary fusion science and technology, conducts professional meetings, and disseminates technical information in support of these goals. Members focus on the assessment and resolution of critical developmental issues for practical fusion energy applications.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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Latest News
G7 pledges support for nuclear at Italy meeting
The Group of Seven (G7) recommitted its support for nuclear energy in the countries that opt to use it at a Ministerial Meeting on Climate in Italy last month.
In a statement following the April meeting, the group committed to support multilateral efforts to strengthen the resilience of nuclear supply chains, referencing the goal set by 25 countries during last year’s COP28 climate conference in Dubai to triple global nuclear generating capacity by 2050.
Taro Ueki
Nuclear Science and Engineering | Volume 194 | Number 6 | June 2020 | Pages 422-432
Technical Paper | 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.