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Robotics & Remote Systems
The Mission of the Robotics and Remote Systems Division is to promote the development and application of immersive simulation, robotics, and remote systems for hazardous environments for the purpose of reducing hazardous exposure to individuals, reducing environmental hazards and reducing the cost of performing work.
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2024 ANS Winter Conference and Expo
November 17–21, 2024
Orlando, FL|Renaissance Orlando at SeaWorld
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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New laws offer nuclear industry incentives for existing power plant uprates
This year, the U.S. nuclear industry received a much-needed economic boost that could help preserve operating nuclear power plants and incentivize upgrades that extend their lifespan and power output.
Signed into law in 2022, the Inflation Reduction Act offers production tax credits (PTCs) for existing nuclear power plants and either PTCs or investment tax credits (ITCs) for new carbon-free generation. These credits could make power uprates—increasing the maximum power level at which a commercial plant may operate—a much more appealing option for utilities.
S. K. Fraley, T. J. Hoffman
Nuclear Science and Engineering | Volume 70 | Number 1 | April 1979 | Pages 14-19
Technical Paper | doi.org/10.13182/NSE79-A18923
Articles are hosted by Taylor and Francis Online.
Two methods to improve the variance of statistical flux-at-a-point estimators over conventional unbounded estimators are developed that are readily implemented in multigroup Monte Carlo radiation transport computer codes. The theory behind the methods is developed, and the procedures for their application to Monte Carlo computer codes are outlined where necessary for clarity. Their application is demonstrated by the solution of a sample problem. These methods do not require a modification of the random walk, are easily implemented in multigroup Monte Carlo computer codes, and provide results that are comparable to other finite variance techniques.