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Division Spotlight
Radiation Protection & Shielding
The Radiation Protection and Shielding Division is developing and promoting radiation protection and shielding aspects of nuclear science and technology — including interaction of nuclear radiation with materials and biological systems, instruments and techniques for the measurement of nuclear radiation fields, and radiation shield design and evaluation.
Meeting Spotlight
2025 ANS Annual Conference
June 15–18, 2025
Chicago, IL|Chicago Marriott Downtown
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The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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BREAKING NEWS: Trump issues executive orders to overhaul nuclear industry
The Trump administration issued four executive orders today aimed at boosting domestic nuclear deployment ahead of significant growth in projected energy demand in the coming decades.
During a live signing in the Oval Office, President Donald Trump called nuclear “a hot industry,” adding, “It’s a brilliant industry. [But] you’ve got to do it right. It’s become very safe and environmental.”
U. B. Phathanapirom, E. A. Schneider
Nuclear Science and Engineering | Volume 182 | Number 4 | April 2016 | Pages 502-522
Technical Paper | doi.org/10.13182/NSE15-25
Articles are hosted by Taylor and Francis Online.
This paper introduces a new methodology for explicitly incorporating uncertainties in key parameters into decision making regarding the transition between various nuclear fuel cycles. These key uncertainties—in demand growth rates, technology availability, and technology costs, among others—are unlikely to be resolved for several decades and invalidate the concept of planning for a unique optimal transition strategy. Past time-dependent analyses of the nuclear fuel cycle have confronted uncertainties by using a scenario-based approach where key variables are parametrically varied, which gives rise to inflexible courses of action associated with optima for each scenario. Instead, this work selects hedging strategies through a decision making under uncertainty framework. These strategies are found by applying a choice criterion to select courses of action that mitigate regrets. These regrets are calculated by evaluating the performance of all possible transition strategies for every feasible outcome of the uncertain parameter(s). The methodology is applied to a case study involving transition from the current once-through light water reactor fuel cycle to one relying on continuous recycle in fast reactors, and the effect of choice criterion is explored. Hedging strategies are found that preserve significant flexibility to allow alteration of the fuel cycle strategy once these uncertainties are resolved. This work may provide guidance for agent-based, behavioral modeling in fuel cycle simulators as well as decision making in real-world applications.