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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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Fusion Science and Technology
August 2025
Latest News
The newest era of workforce development at ANS
As most attendees of this year’s ANS Annual Conference left breakfast in the Grand Ballroom of the Chicago Downtown Marriott to sit in on presentations covering everything from career pathways in fusion to recently digitized archival nuclear films, 40 of them made their way to the hotel’s fifth floor to take part in the second offering of Nuclear 101, a newly designed certification course that seeks to give professionals who are in or adjacent to the industry an in-depth understanding of the essentials of nuclear energy and engineering from some of the field’s leading experts.
Masahiro Kinoshita
Fusion Science and Technology | Volume 9 | Number 3 | May 1986 | Pages 492-498
Technical Paper | Tritium System | doi.org/10.13182/FST86-A24736
Articles are hosted by Taylor and Francis Online.
An efficient dynamic simulation code for hydrogen isotope distillation columns is developed. Because of the great dimensionality and stiffness of the basic ordinary differential equations to be integrated, the long computing time required is often the major stumbling block in computer simulation work for column dynamics. Publicly available integration algorithms are reviewed and some are tested. The Ballard-Brosilow algorithm is chosen as the most attractive one in terms of both stability and simplicity. The algorithm requires only solution of linear tridiagonal equations and scalar bubble point calculations at every time step. Replacing the improved Euler algorithm in the previous code by the Ballard-Brosilow algorithm and determining an adjustment method for the time step size, the resultant computer code presents a remarkable success: A typical numerical example simulating column dynamics from a steady state to another indicates that the calculational results can be obtained with engineering accuracy in about two orders of magnitude shorter computing time.