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Division Spotlight
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.
Meeting Spotlight
Utility Working Conference and Vendor Technology Expo (UWC 2024)
August 4–7, 2024
Marco Island, FL|JW Marriott Marco Island
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
ARPA-E announces $40 million to develop transmutation technologies for UNF
The Department of Energy’s Advanced Research Projects Agency–Energy (ARPA-E) announced $40 million in funding to develop cutting-edge technologies to enable the transmutation of used nuclear fuel into less-radioactive substances. According to ARPA-E, the new initiative addresses one of the agency’s core goals as outlined by Congress: to provide transformative solutions to improve the management, cleanup, and disposal of radioactive waste and spent nuclear fuel.
Thomas M. Sutton
Nuclear Science and Engineering | Volume 185 | Number 1 | January 2017 | Pages 174-183
Technical Paper | doi.org/10.13182/NSE15-131
Articles are hosted by Taylor and Francis Online.
In the study of Monte Carlo statistical uncertainties for iterated-fission-source calculations, an important distinction is made between the real and the apparent variances. The former is the actual variance of a Monte Carlo calculation result, while the latter is an estimate of the former obtained using the results of the fission generations in the formula for uncorrelated random variates. For years it has been known that the apparent variance is a biased estimate of the real variance, and the reason for the bias has been understood. More recently, several authors have noted various interesting phenomena regarding the apparent and the real variances and the relationships among them. Some of these are an increase in the apparent variance near surfaces with reflecting boundary conditions, a nonuniform spatial distribution of the ratio of the apparent-to-real variance, the dependence of this ratio on the size of the region over which the result is tallied, and a rate of convergence of the real variance that is less than the inverse of the number of neutron histories run. This paper discusses a theoretical description of the Monte Carlo process using a discretized phase-space and then uses it to explain the causes of these phenomena.