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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
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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Nuclear Science and Engineering
June 2025
Nuclear Technology
May 2025
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Latest News
EnergySolutions to help explore advanced reactor development in Utah
Utah-based waste management company EnergySolutions announced that it has signed a memorandum of understating with the Intermountain Power Agency and the state of Utah to explore the development of advanced nuclear power generation at the Intermountain Power Project (IPP) site near Delta, Utah.
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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