ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
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Division Spotlight
Thermal Hydraulics
The division provides a forum for focused technical dialogue on thermal hydraulic technology in the nuclear industry. Specifically, this will include heat transfer and fluid mechanics involved in the utilization of nuclear energy. It is intended to attract the highest quality of theoretical and experimental work to ANS, including research on basic phenomena and application to nuclear system design.
Meeting Spotlight
2025 ANS Annual Conference
June 15–18, 2025
Chicago, IL|Chicago Marriott 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
July 2025
Nuclear Technology
June 2025
Fusion Science and Technology
Latest News
Former NRC commissioners lend support to efforts to eliminate mandatory hearings
A group of nine former nuclear regulatory commissioners sent a letter Wednesday to the current Nuclear Regulatory Commission members lending support to efforts to get rid of mandatory hearings in the licensing process, which should speed up the process by three to six months and save millions of dollars.
Advances in Thermal Hydraulics (ATH 2022)
Technical Session
Tuesday, June 14, 2022|10:15AM–12:00PM PDT|Redondo
Session Chair:
Nadish Saini
Alternate Chair:
Yue Jin
Session Organizer:
W. David Pointer
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Embedded Fiber Optic Smart Parts Towards Advanced Reactor Applications
Andrew J. Boulanger (Luna Innovation), S. Derek Rountree (Luna Innovation), Connor Donlan (Virginia Commonwealth Univ.), Arturo Cabral (Virginia Commonwealth Univ.), Lane B. Carasik (Virginia Commonwealth Univ.), Adam Hehr (Fabrisonic)
Paper
Deep Learning-Based System Diagnosis for Nuclear Power Plant Using Infrared Thermal Cameras
Ik Jae Jin (Ulsan Nat'l Institute of Science and Technology), Do Yeong Lim (Ulsan Nat'l Institute of Science and Technology), In Cheol Bang (Ulsan Nat'l Institute of Science and Technology)
Machine Learning-Based Prediction of Departure from Nucleate Boiling Power for the PSBT Benchmark
Chaitee Godbole (NCSU), Gregory Delipei (NCSU), Xu Wu (NCSU), Maria Avramova (NCSU), Upendra Rohatgi (Brookhaven)
Prediction of Minimum Film Boiling Temperature Using a Physics-Informed Machine Learning-Aided Framework
K.M. Kim (Virginia Tech), P. Hurley (Virginia Tech), J.P. Duarte (Virginia Tech)
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