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Decommissioning & Environmental Sciences
The mission of the Decommissioning and Environmental Sciences (DES) Division is to promote the development and use of those skills and technologies associated with the use of nuclear energy and the optimal management and stewardship of the environment, sustainable development, decommissioning, remediation, reutilization, and long-term surveillance and maintenance of nuclear-related installations, and sites. The target audience for this effort is the membership of the Division, the Society, and the public at large.
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2024 ANS Annual Conference
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Las Vegas, NV|Mandalay Bay Resort and Casino
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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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Latest News
Securing the advanced reactor fleet
Physical protection accounts for a significant portion of a nuclear power plant’s operational costs. As the U.S. moves toward smaller and safer advanced reactors, similar protection strategies could prove cost prohibitive. For tomorrow’s small modular reactors and microreactors, security costs must remain appropriate to the size of the reactor for economical operation.
Henry Lichtenstein
Nuclear Science and Engineering | Volume 133 | Number 3 | November 1999 | Pages 258-268
Technical Paper | doi.org/10.13182/NSE99-A2086
Articles are hosted by Taylor and Francis Online.
An adaptive reduced-source approach is utilized for a Monte Carlo transport solution for the one-speed finite slab problem in [x,] geometry. Although a solution for the underlying problem has been available to arbitrary precision for some time, the purpose here is to demonstrate how the convergence afforded by traditional (nonadaptive) Monte Carlo can be improved significantly, without compromising its precision. It is demonstrated that the reduced-source Monte Carlo technique obtains multiple-orders-of-magnitude improvement over traditional Monte Carlo convergence for the two-dimensional transport problem treated. The goal is that ongoing research will obtain exponential convergence for practical applications that are not tractable with methodology currently available.