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 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
Latest Magazine Issues
Mar 2026
Jan 2026
Latest Journal Issues
Nuclear Science and Engineering
March 2026
Nuclear Technology
February 2026
Fusion Science and Technology
April 2026
Latest News
Aalo Atomics discusses the road ahead
Yasir Arafat, president and chief technology officer of Aalo Atomics, participated in the first day of sessions at the Nuclear Regulatory Commission’s annual Regulatory Information Conference (RIC). There, he recapped some of the company’s recent milestones and revealed new details on what lies ahead for Aalo.
His attendance at the event coincided with a number of announcements in the past two weeks. Those announcements covered new contracts with Global Nuclear Fuel and Baker Hughes, the release of a new strategic roadmap, the completion of fuel enrichment by Urenco USA, and a new approval from the Department of Energy.
J. Louis Tylee
Nuclear Technology | Volume 61 | Number 1 | April 1983 | Pages 25-32
Technical Paper | Nuclear Safety | doi.org/10.13182/NT83-A33140
Articles are hosted by Taylor and Francis Online.
A simple real-time model of the loss-of-fluid test (LOFT) reactor is derived and used to predict reactor performance during an anticipated transient without scram (ATWS). The developed model consists of only six nonlinear differential equations. Model states are precursor concentrations of two delayed neutron groups, average fuel and cladding temperatures, average core coolant temperature, and measured reactor outlet temperature. Ancillary dynamic descriptions of a hot fuel rod allow computation of peak rod temperatures. Comparing model calculations to actual LOFT ATWS measurements demonstrates the model’s phenomenological accuracy.