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Division members promote the advancement of mathematical and computational methods for solving problems arising in all disciplines encompassed by the Society. They place particular emphasis on numerical techniques for efficient computer applications to aid in the dissemination, integration, and proper use of computer codes, including preparation of computational benchmark and development of standards for computing practices, and to encourage the development on new computer codes and broaden their use.
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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
IAEA promoting nuclear energy with G20
The International Atomic Energy Agency launched a collaboration with the Group of 20 this week to highlight the key role that nuclear energy can play in achieving energy security and climate-change goals.
The aim of this first-of-its-kind partnership with G20—the world’s largest economic group—is to build momentum for nuclear power. This is the first time the IAEA has presented to G20 on issues relating to nuclear power.
Kaushik Banerjee, William R. Martin
Nuclear Science and Engineering | Volume 174 | Number 1 | May 2013 | Pages 30-45
Technical Paper | doi.org/10.13182/NSE11-94
Articles are hosted by Taylor and Francis Online.
Monte Carlo point detector and surface crossing flux tallies are two widely used tallies, but they suffer from an unbounded variance. As a result, the central limit theorem cannot be used for these tallies to estimate confidence intervals. By construction, kernel density estimator (KDE) tallies can be directly used to estimate flux at a point, but the variance of this point estimate does not converge as 1/N, which is not unexpected for a point quantity. However, an improved approach is to modify both point detector and surface crossing flux tallies directly by using KDE within a variance reduction approach and taking advantage of the fact that KDE estimates the underlying probability density function. This methodology is illustrated by several numerical examples and shows numerically that both the surface crossing tally and the point detector tally converge as 1/N (in variance), and both are asymptotically unbiased.