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Division Spotlight
Education, Training & Workforce Development
The Education, Training & Workforce Development Division provides communication among the academic, industrial, and governmental communities through the exchange of views and information on matters related to education, training and workforce development in nuclear and radiological science, engineering, and technology. Industry leaders, education and training professionals, and interested students work together through Society-sponsored meetings and publications, to enrich their professional development, to educate the general public, and to advance nuclear and radiological science and engineering.
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!
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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.
A. Melintescu, D. Galeriu
Fusion Science and Technology | Volume 54 | Number 1 | July 2008 | Pages 269-272
Technical Paper | Environment and Safety | doi.org/10.13182/FST08-A1810
Articles are hosted by Taylor and Francis Online.
In the frame of IAEA EMRAS (Environmental Modelling for Radiation Safety) programme, there was developed a scenario for models' testing starting with unpublished data for a sow fed with OBT for 84 days. The scenario includes model predictions for the dynamics of tritium in urine and faeces and HTO and OBT in organs at sacrifice. There have been done two inter-comparison exercises and most of the models succeeded to give predictions better than a factor 3 to 5, excepting faeces. There has been done an analysis of models' structure, performance and limits in order to be able to build a model of moderate complexity with a reliable predictive power, able to be applied for human dosimetry, also, when OBT data are missing.