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
Accelerator Applications
The division was organized to promote the advancement of knowledge of the use of particle accelerator technologies for nuclear and other applications. It focuses on production of neutrons and other particles, utilization of these particles for scientific or industrial purposes, such as the production or destruction of radionuclides significant to energy, medicine, defense or other endeavors, as well as imaging and diagnostics.
Meeting Spotlight
International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C 2025)
April 27–30, 2025
Denver, CO|The Westin Denver Downtown
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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Latest News
Sam Altman steps down as Oklo board chair
Advanced nuclear company Oklo Inc. has new leadership for its board of directors as billionaire Sam Altman is stepping down from the position he has held since 2015. The move is meant to open new partnership opportunities with OpenAI, where Altman is CEO, and other artificial intelligence companies.
Mengkun Li, Guanxiang Wei, Zhihui Xu, Jun Wang, Ming Yang
Nuclear Science and Engineering | Volume 194 | Number 6 | June 2020 | Pages 447-461
Technical Paper | doi.org/10.1080/00295639.2019.1710975
Articles are hosted by Taylor and Francis Online.
This study introduces a radiation avoidance algorithm to help radiological occupational personnel (ROP) avoid high radiation exposure in a radioactive environment. The premise of this study is that ROP can be designated as a movable point in a two-dimensional radioactive scene with known radioactive sources. A trajectory of ROP is generated by the radiation avoidance algorithm based on an artificial potential field (APF) and particle swarm optimization (PSO). In the algorithm, ROP is subjected to an attractive force from a target as well as multiple repulsive forces from multiple radioactive sources. The attractive force and repulsive forces drive ROP moving toward the target along the trajectory. APF has obvious difficulties with parameter selection and a local minima problem. So, we used the PSO algorithm to solve these difficulties of APF. Additionally, we developed a radiation avoidance simulation program using the C# programming language. Simulation experiments showed the proposed algorithm could be useful to meet the challenges of radiation avoidance applications that can be described as trajectory optimization problems.