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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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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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Fusion Science and Technology
Latest News
Taking shape: Fusion energy ecosystems built with public-private partnerships
It’s possible to describe fusion in simple terms: heat and squeeze small atoms to get abundant clean energy. But there’s nothing simple about getting fusion ready for the grid.
Private developers, national lab and university researchers, suppliers, and end users working toward that goal are developing a range of complex technologies to reach fusion temperatures and pressures, confounded by science and technology gaps linked to plasma behavior; materials, diagnostics, and electronics for extreme environments; fuel cycle sustainability; and economics.
Dan G. Cacuci, Mihaela Ionescu-Bujor
Nuclear Science and Engineering | Volume 165 | Number 1 | May 2010 | Pages 1-17
Technical Paper | doi.org/10.13182/NSE09-37A
Articles are hosted by Taylor and Francis Online.
When n measurements and/or computations of the same (unknown) quantity yield data points xj with corresponding standard deviations (uncertainties) j such that the distances [vertical bar]xj - xk[vertical bar] between any two data points are smaller than or comparable to the sum (j + k) of their respective uncertainties, the respective data points are considered to be consistent or to agree within error bars. However, when the distances [vertical bar]xj - xk[vertical bar] are larger than (j + k), the respective data are considered to be inconsistent or discrepant. Inconsistencies can be caused by unrecognized or ill-corrected experimental effects (e.g., background corrections, dead time of the counting electronics, instrumental resolution, sample impurities, calibration errors). Although there is a nonzero probability that genuinely discrepant data could occur (for example, for a Gaussian sampling distribution with standard deviation , the probability that two equally precise measurements would be separated by more than 2 is erfc(1) [approximately equal] 0.157), it is much more likely that apparently discrepant data actually indicate the presence of unrecognized errors.This work addresses the treatment of unrecognized errors by applying the maximum entropy principle under quadratic loss, to the discrepant data. Novel results are obtained for the posterior distribution determining the unknown mean value (i.e., unknown location parameter) of the data and also for the marginal posterior distribution of the unrecognized errors. These novel results are considerably more rigorous, are more accurate, and have a wider range of applicability than extant recipes for handling discrepant data.