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Division Spotlight
Mathematics & Computation
Division members promote the advancement of mathematical and computational methods for solving problems arising in all disciplines encompassed by the Society. They place particular emphasis on numerical techniques for efficient computer applications to aid in the dissemination, integration, and proper use of computer codes, including preparation of computational benchmark and development of standards for computing practices, and to encourage the development on new computer codes and broaden their use.
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.”
Rodney R. Gay
Nuclear Science and Engineering | Volume 83 | Number 1 | January 1983 | Pages 1-12
Technical Paper | doi.org/10.13182/NSE83-A17984
Articles are hosted by Taylor and Francis Online.
The GFLOW code analyzes a three-dimensional rectangular porous medium by dividing the porous medium into a number of nodes or cells specified by the user. The finite difference form of the fluid conservation equations is solved for each node by application of a modified “marker and cell” numerical technique. The existence of spent nuclear fuel in any node is modeled by using a porosity value less than unity in that node and by including a surface heat transfer term in the fluid energy equation. In addition, local pressure losses due to grid spaces or other planar flow obstructions can be modeled by local loss coefficients. Heat conduction in the fuel is simulated by a fast running implicit finite difference model of the fuel, gap, and clad regions of the fuel rod.