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Fusion Energy
This division promotes the development and timely introduction of fusion energy as a sustainable energy source with favorable economic, environmental, and safety attributes. The division cooperates with other organizations on common issues of multidisciplinary fusion science and technology, conducts professional meetings, and disseminates technical information in support of these goals. Members focus on the assessment and resolution of critical developmental issues for practical fusion energy applications.
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ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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
In an international industry, regulators cross the border too
Since nuclear physics works the same in Ontario as it does in Tennessee, the industry has been trying to create a reactor that can be deployed on both sides of the border. Now, the Nuclear Regulatory Commission and the Canadian Nuclear Safety Commission have decided that some of their rulings can cross the border too.
Dmitriy Y. Anistratov
Nuclear Science and Engineering | Volume 174 | Number 2 | June 2013 | Pages 150-162
Technical Paper | doi.org/10.13182/NSE12-28
Articles are hosted by Taylor and Francis Online.
The nonlinear diffusion acceleration (NDA) method is an efficient and flexible transport iterative scheme for solving reactor-physics problems. This paper presents a fast iterative algorithm for solving multigroup neutron transport eigenvalue problems in one-dimensional slab geometry. The proposed method is defined by a multilevel system of equations that includes multigroup and effective one-group low-order NDA equations. The eigenvalue is evaluated in an exact projected solution space of the smallest dimensionality. Numerical results that illustrate the performance of the new algorithm are demonstrated.
