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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.
Bart L. Sjenitzer, J. Eduard Hoogenboom
Nuclear Science and Engineering | Volume 175 | Number 1 | September 2013 | Pages 94-107
Technical Paper | doi.org/10.13182/NSE12-44
Articles are hosted by Taylor and Francis Online.
In nuclear reactor physics, deterministic and hybrid calculation methods dominate the field of transient analysis. This implies that important safety assessments are subject to many approximations, which are needed by these methods. This paper proposes the Dynamic Monte Carlo method (Dynamic MC), which solves the coupled Boltzmann and kinetic equations with exact geometry and continuous energy, using only Monte Carlo techniques.For Dynamic MC a number of new techniques are developed, e.g., precursor tracking, forced decay for precursors, and the branchless method. Also, the particle source of the simulation has to be determined differently from what is current standard Monte Carlo practice, and the simulation scheme is adapted.A few example cases are simulated, demonstrating the effectiveness of Dynamic MC. The sample cases vary from simple homogeneous systems to full fuel assemblies with an asymmetric flux profile during the transient. Since Dynamic MC is implemented in the general-purpose Monte Carlo code Tripoli, it can be applied to any geometry.