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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
2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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
Can hydrogen be the transportation fuel in an otherwise nuclear economy?
Let’s face it: The global economy should be powered primarily by nuclear power. And it probably will by the end of this century, with a still-significant assist from renewables and hydro. Once nuclear systems are dominant, the costs come down to where gas is now; and when carbon emissions are reduced to a small portion of their present state, it will become obvious that most other sources are only good in niche settings. I mean, why use small modular reactors to load-follow when they can just produce that power instead of buffering it?
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.