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 Winter Conference & Expo
November 15–18, 2026
Phoenix, AZ|Arizona Grand Resort & Spa
Latest Magazine Issues
Aug 2026
Jan 2026
2026
Latest Journal Issues
Nuclear Science and Engineering
October 2026
Nuclear Technology
September 2026
Fusion Science and Technology
August 2026
Latest News
LLNL, Ampera partner to develop thorium-based TRISO fuel
Lawrence Livermore National Laboratory has formed a strategic partnership with Ampera to develop the company’s nuclear fuel concept through a project named THUNDER, for Thorium Unimodal Droplet Ejection for Reactors.
The focus of THUNDER is fabricating TRISO made with kernels of thorium rather than the usual uranium. LLNL and Ampera will evaluate and optimize liquid metal–jetting technology to produce highly uniform, spherical kernels of thorium-232 for later processing into TRISO fuel.
James F. Harrison
Nuclear Technology | Volume 83 | Number 3 | December 1988 | Pages 310-324
Technical Paper | Fifth International Retran Meeting / Heat Transfer and Fluid Flow | doi.org/10.13182/NT88-A34144
Articles are hosted by Taylor and Francis Online.
An assessment of RETRAN’s ability to provide best-estimate reference information for the qualification of full-scope power plant training simulators is provided. Analyses that compare RETRAN predictions to plant data or to test facility data are summarized. The relationship between the RETRAN qualification studies and the simulator test matrix presented in Electric Power Research Institute NP-4243, Analytic Simulator Qualification Methodology, and the requirements of ANSI/ANS-3.5 are discussed. Thirty-one boiling water reactor transient analyses and 50 pressurized water reactor analyses have been evaluated. The evaluation shows that RETRAN models have experienced essentially all of the “dynamic states” required for the qualification of power plant training simulators. The rating for the magnitude, timing, and trend measures indicates that the predictions using RETRAN models are either completely acceptable or acceptable with some reservations most of the time. The magnitude performance varies depending on the type of event, whereas the trend and timing performance is nearly the same for all event types. The ratings for the RETRAN transient predictions show that RETRAN models are capable of predicting the important system parameters with the fidelity required for the qualification of training simulators.