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Division Spotlight
Fuel Cycle & Waste Management
Devoted to all aspects of the nuclear fuel cycle including waste management, worldwide. Division specific areas of interest and involvement include uranium conversion and enrichment; fuel fabrication, management (in-core and ex-core) and recycle; transportation; safeguards; high-level, low-level and mixed waste management and disposal; public policy and program management; decontamination and decommissioning environmental restoration; and excess weapons materials disposition.
Meeting Spotlight
2025 ANS Annual Conference
June 15–18, 2025
Chicago, IL|Chicago Marriott Downtown
Standards Program
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.”
C. Smidts
Nuclear Science and Engineering | Volume 112 | Number 2 | October 1992 | Pages 114-126
Technical Paper | doi.org/10.13182/NSE92-A28408
Articles are hosted by Taylor and Francis Online.
An example is given to illustrate the probabilistic reactor dynamics theory developed earlier. A reservoir with two output valves is considered in which the valves are subject to random failures. The operator must maintain the tank pressure within an upper and a lower bound whatever the initial system state may be. A complete description is given of the physical system, of the instrumentation, and of the human model that was selected to describe the operator’s behavior. The results are expressed in terms of state occupation probabilities and mean exit times. A Monte Carlo algorithm is briefly described.