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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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2024 ANS Annual Conference
June 16–19, 2024
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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Proving DRACO will deliver
The United States is now closer than it has been in over five decades to launching the first nuclear thermal rocket into space, thanks to DRACO—the Demonstration Rocket for Agile Cislunar Orbit.
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.