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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
Conference on Nuclear Training and Education: A Biennial International Forum (CONTE 2025)
February 3–6, 2025
Amelia Island, FL|Omni Amelia Island Resort
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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Jan 2025
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Nuclear Science and Engineering
February 2025
Nuclear Technology
Fusion Science and Technology
Latest News
Feinstein Institutes to research novel radiation countermeasure
The Feinstein Institutes for Medical Research, home of the research institutes of New York’s Northwell Health, announced it has received a five-year, $2.9 million grant from the National Institutes of Health to investigate the potential of human ghrelin, a naturally occurring hormone, as a medical countermeasure against radiation-induced gastrointestinal syndrome (GI-ARS).
Technical Session|Sponsored by MSTD
Thursday, June 11, 2020|10:00–11:45AM EDT
Session Chair:
Kenneth J. Geelhood
Session Organizer:
Alternate Chair:
Kallie E. Metzger
Staff Producer:
Jay Bogardus (American Nuclear Society)
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Performance Analysis of Silicon Carbide Composite Clad Uranium Carbide Fuel during Reactivity Initiated Accident
Hangbok Choi (General Atomics), John Bolin (General Atomics)
Paper
Microstructural Analysis of the SiC Layer of Tristructural-Isotropic Particles in High-Temperature Steam Atmospheres
Katherine Montoya (Univ. of Texas, San Antonio), Brian A. Brigham (Univ. of Texas, San Antonio), Tyler J. Gerczak (ORNL), Elizabeth Sooby Wood (Univ. of Texas, San Antonio)
Using Machine Learning to Predict the Oxidation of Graphite
Cole Moczygemba (Univ. of Texas, San Antonio), Michael Geyer (Univ. of Texas, San Antonio), Amanda Fernandez (Univ. of Texas, San Antonio), Elizabeth Sooby (Univ. of Texas, San Antonio)
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