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2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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Empowering the next generation: ANS’s newest book focuses on careers in nuclear energy
A new career guide for the nuclear energy industry is now available: The Nuclear Empowered Workforce by Earnestine Johnson. Drawing on more than 30 years of experience across 16 nuclear facilities, Johnson offers a practical, insightful look into some of the many career paths available in commercial nuclear power. To mark the release, Johnson sat down with Nuclear News for a wide-ranging conversation about her career, her motivation for writing the book, and her advice for the next generation of nuclear professionals.
When Johnson began her career at engineering services company Stone & Webster, she entered a field still reeling from the effects of the Three Mile Island incident in 1979, nearly 15 years earlier. Her hiring cohort was the first group of new engineering graduates the company had brought on since TMI, a reflection of the industry-wide pause in nuclear construction. Her first long-term assignment—at the Millstone site in Waterford, Conn., helping resolve design issues stemming from TMI—marked the beginning of a long and varied career that spanned positions across the country.
Chih-Ming Tsai, Shih-Jen Wang, Show-Chyuan Chiang
Nuclear Technology | Volume 172 | Number 3 | December 2010 | Pages 237-245
Technical Paper | Reactor Safety | doi.org/10.13182/NT10-A10932
Articles are hosted by Taylor and Francis Online.
The modular accident analysis program (MAAP) is a fast-running severe accident analysis tool with which the timing of key events and source terms in a severe accident are assessed. The idea of combining MAAP and an optimization algorithm to identify the realistic accident parameters in terms of minimizing the discrepancies between the plant data and the simulation results is straightforward. In 2008 Chien and Wang first compiled the combination of the MAAP4 source codes and a Simplex code as a computer-aided tool for the loss-of-coolant accident (LOCA) of the Kuosheng nuclear power plant (NPP). The break area and break elevation were successfully identified. However, in that approach to putting the idea into practice was that hard data dependence exists between MAAP and the optimization algorithm. Tedious tracing and modification work is required to ensure all plant variables in MAAP source codes with the exception of the adjusted accident parameters are identical at the beginning of every simulation. The plant- and accident-specific development features also easily limit the applications of this idea to the nuclear industry, like being boxed in.In this study a so-called "out-of-box" approach is proposed that can omit the limits of the idea applications on severe accident management. A parameter identification tool developed in this approach for the same postulated LOCA of the Kuosheng NPP is carried out for verification and validation. It demonstrates the advantages of successful parameter identification, less programming efforts, and no plant- and accident-specific features.