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Division Spotlight
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.
Meeting Spotlight
ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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
Norway’s Halden reactor takes first step toward decommissioning
The government of Norway has granted the transfer of the Halden research reactor from the Institute for Energy Technology (IFE) to the state agency Norwegian Nuclear Decommissioning (NND). The 25-MWt Halden boiling water reactor operated from 1958 to 2018 and was used in the research of nuclear fuel, reactor internals, plant procedures and monitoring, and human factors.
Ross Pivovar, Ole Wieckhorst
Nuclear Technology | Volume 205 | Number 7 | July 2019 | Pages 945-950
Regular Technical Paper | doi.org/10.1080/00295450.2018.1548220
Articles are hosted by Taylor and Francis Online.
All licensable critical heat flux (CHF) correlations/regressions models must determine and demonstrate a “design limit” that bounds the CHF correlation predicted/measured residuals via a 95/95 tolerance limit. This is a quick and straightforward calculation when the residuals are well behaved, exhibiting no trends and no heteroscedasticity. However, as models become increasingly complex and as required parameter ranges become more extended, the likelihood of nonconservative subregions increases. A suggested solution from the open literature is the overly conservative approach of basing the design limit on the subregion with the largest variance. This approach unavoidably overly constrains the overall regression model and often is too conservative for subregions due to a loss in degrees of freedom. Quantile regressions alleviate these issues by smoothly varying the design limit based on covariates and adapting to each subregion. Thus, a quantile regression achieves the objective of appropriately bounding all subregions without overly biasing the overall regression model.