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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 Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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
G7 pledges support for nuclear at Italy meeting
The Group of Seven (G7) recommitted its support for nuclear energy in the countries that opt to use it at a Ministerial Meeting on Climate in Italy last month.
In a statement following the April meeting, the group committed to support multilateral efforts to strengthen the resilience of nuclear supply chains, referencing the goal set by 25 countries during last year’s COP28 climate conference in Dubai to triple global nuclear generating capacity by 2050.
Dumitru Serghiuta, John Tholammakkil
Nuclear Technology | Volume 205 | Number 12 | December 2019 | Pages 1513-1528
Critical Review | doi.org/10.1080/00295450.2019.1570751
Articles are hosted by Taylor and Francis Online.
This paper reviews the attributes and challenges of applying the functional failure concept and the use of Best-Estimate Plus Uncertainty methods in evaluating protective systems in the risk space. As an illustrative example, the paper uses the case of the effectiveness of CANada Deuterium Uranium (CANDU) reactor shutdown systems. A risk-informed formulation is first introduced for estimation of a reasonable limit for functional failure probability using the Swiss Cheese model. In the real application, there are several challenges in realistically estimating probabilities of exceeding a prescribed design or regulatory limit. Key challenges discussed in this critical review include the use of complex, computationally intensive predictive models; modeling completeness; assumptions about input distributions; validation; separation of uncertainties; and selection of statistical model and algorithms. The use of hybrid deterministic-probabilistic methods may address these challenges to a certain extent.