ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
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
2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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!
Latest Magazine Issues
Apr 2024
Jan 2024
Latest Journal Issues
Nuclear Science and Engineering
May 2024
Nuclear Technology
Fusion Science and Technology
Latest News
X-energy receives federal tax credit for TRISO fuel facility
Advanced reactor company X-energy has been awarded $148.5 million in tax credits under the Inflation Reduction Act for construction of its TRISO-X fuel fabrication facility in Oak Ridge, Tenn.
Jeffrey A. Favorite
Nuclear Science and Engineering | Volume 177 | Number 3 | July 2014 | Pages 361-366
Technical Note | doi.org/10.13182/NSE13-66
Articles are hosted by Taylor and Francis Online.
Particle fluxes on surfaces are difficult to calculate with Monte Carlo methods because the score requires a division by the surface-crossing angle cosine, and grazing angles lead to inaccuracies. The traditional method for dealing with this problem was recently extended by recognizing the assumptions that were implicit in its derivation. More recently, a kernel density estimator (KDE) has been proposed to replace the traditional method. In this technical note, example problems from the KDE development are analyzed, and the failure of the traditional method is shown to be due to the invalidity of one of the implicit assumptions, as previously predicted, and the extended theory is used to correct the traditional method.