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Division Spotlight
Materials Science & Technology
The objectives of MSTD are: promote the advancement of materials science in Nuclear Science Technology; support the multidisciplines which constitute it; encourage research by providing a forum for the presentation, exchange, and documentation of relevant information; promote the interaction and communication among its members; and recognize and reward its members for significant contributions to the field of materials science in nuclear technology.
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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Latest News
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.”
Allen J. Toreja, Rizwan-uddin
Nuclear Science and Engineering | Volume 142 | Number 1 | September 2002 | Pages 85-95
Technical Note | doi.org/10.13182/NSE02-A2290
Articles are hosted by Taylor and Francis Online.
Adaptive mesh refinement capability has been developed and implemented for the time-dependent nodal integral method (NIM). The combination of adaptive mesh refinement (AMR) with the NIM maintains the coarse mesh efficiency of the nodal method by allowing high resolution only in regions where it is needed. Furthermore, exploiting certain features of the nodal method, such as using transverse-integrated variables for efficient error estimation and using node interior reconstruction to develop accurate interpolation operators, can enhance the AMR process. In this work, the NIM-AMR is formally developed, and applications of the NIM-AMR to convection-diffusion problems are presented. Results show that for a given accuracy, the NIM-AMR can be several times faster than the NIM alone.