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Conference Spotlight
2026 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
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Latest News
DOE announces “monumental step” in SRS target recovery program
The Department of Energy has announced the successful transfer of the first Mark-18A target from the Savannah River Site to Savannah River National Laboratory, marking “the beginning of operations for a newly established radiochemical separation capability to recover valuable isotopes.” The agency stated that the Mark-18A Target Recovery Program—which involves the DOE National Nuclear Security Administration, the Office of Environmental Management, and the Office of Science—is demonstrating “how legacy materials previously destined for disposal can be recovered and transformed into valuable resources.”
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.