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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.
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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.”
Keqiang Ruan, Xiaogang Xue, Xuedong Fu
Nuclear Science and Engineering | Volume 139 | Number 1 | September 2001 | Pages 105-110
Technical Note | doi.org/10.13182/NSE01-A2225
Articles are hosted by Taylor and Francis Online.
An alternate formulation of the two-group transverse-integration-based nodal expansion method is presented. In this formulation, the two-group problem is formulated by using the relationship between the group fluxes derived from an analytical procedure. As a result, a simplified procedure for the thermal group is suggested. The numerical results of the benchmark problems show that the new formulation of the nodal expansion method has the potential to accurately solve multidimensional problems with a considerable reduction in the computational cost required by the conventional two-group scheme.