ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
Explore membership for yourself or for your organization.
Conference Spotlight
2026 Nuclear Energy Conference & Expo (NECX)
August 24–27, 2026
Dallas, TX|Hilton Anatole
Latest Magazine Issues
Jun 2026
Jan 2026
2026
Latest Journal Issues
Nuclear Science and Engineering
July 2026
Nuclear Technology
June 2026
Fusion Science and Technology
May 2026
Latest News
DOE approves Xcimer’s laser fusion power plant design
The Department of Energy has approved Xcimer Energy's Athena fusion power plant preconceptual technical design. With this milestone achieved, the Denver, Colo.-based company is now moving forward with its plans to develop economical laser inertial confinement fusion using two beamlines, gas laser technology, and a molten salt fusion chamber.
The National Ignition Facility at Lawrence Livermore National Laboratory demonstrated net energy gain from inertial confinement fusion in 2022 using solid-state glass lasers and 192 beamlines.
Technical Session|Sponsored by THD
Wednesday, June 16, 2021|4:30–6:15PM EDT
Session Chair:
Elia Merzari
Alternate Chair:
Guillaume P. Mignot
Session Organizer:
Yassin A. Hassan
Staff Producer:
Jessie Vazquez (ANS)
To access the session recording, you must be logged in and registered for the meeting.
Register NowLog In
To access paper attachments, you must be logged in and registered for the meeting.
Preliminary Safety Analysis Results of Lead Cooled Fast Reactor: MicroURANUS under Unprotected Loss of Flow Condition
Ji Yong Kim (Ulsan Nat'l Institute of Science and Technology), In Cheol Bang (Ulsan Nat'l Institute of Science and Technology)
Paper
Numerical Study of the Heat Transfer in Randomly Packed Spheres for Fluoride Salt Cooled High-Temperature Reactors (FHRs)
Scott Wahlquist (Idaho State Univ.), Amir Ali (Idaho State Univ.)
Unified Domain Knowledge Informed Machine Learning Model for CHF Prediction
Yue Jin (MIT), Xingang Zhao (ORNL), Koroush Shirvan (MIT)