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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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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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Latest News
Nano Nuclear wins Air Force contract for Kronos MMR
New York City–based advanced nuclear technology developer Nano Nuclear Energy has been awarded a Direct-to-Phase II Small Business Innovation Research contract for its Kronos micro modular reactor (MMR) by AFWERX, the innovation and venture arm of the U.S. Air Force. The contract calls for AFWERX, with the 11th Civil Engineering Squadron, to explore the feasibility of deploying the Kronos MMR Energy System at Joint Base Anacostia-Bolling (JBAB) in Washington, D.C.
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.