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Division Spotlight
Nuclear Installations Safety
Devoted specifically to the safety of nuclear installations and the health and safety of the public, this division seeks a better understanding of the role of safety in the design, construction and operation of nuclear installation facilities. The division also promotes engineering and scientific technology advancement associated with the safety of such facilities.
Meeting Spotlight
2024 ANS Winter Conference and Expo
November 17–21, 2024
Orlando, FL|Renaissance Orlando at SeaWorld
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
NRC restores expiration dates for renewed Turkey Point licenses
The Nuclear Regulatory Commission announced this week that it has restored the expiration dates of the Turkey Point nuclear power plant's units 3 and 4 subsequent license renewals (SLR) to July 19, 2052, and April 10, 2053, respectively.
Y. Richet, G. Caplin, J. Crevel, D. Ginsbourger, V. Picheny
Nuclear Science and Engineering | Volume 175 | Number 1 | September 2013 | Pages 1-18
Technical Paper | doi.org/10.13182/NSE11-116
Articles are hosted by Taylor and Francis Online.
Nuclear criticality safety assessment often requires groupwise Monte Carlo simulations of k-effective in order to check subcriticality of the system of interest. A typical task to be performed by safety assessors is hence to find the worst combination of input parameters of the criticality Monte Carlo code (i.e., leading to maximum reactivity) over the whole operating range. Then, checking subcriticality can be done by solving a maximization problem where the input-output map defined by the Monte Carlo code expectation (or an upper quantile) stands for the objective function or “parametric” model. This straightforward view of criticality parametric calculations complies with recent works in Design of Computer Experiments, an active research field in applied statistics. This framework provides a robust support to enhance and consolidate good practices in criticality safety assessment. Indeed, supplementing the standard “expert-driven” assessment by a suitable optimization algorithm may be helpful to increase the reliability of the whole process and the robustness of its conclusions. Such a new safety practice is intended to rely on both well-suited mathematical tools (compliant optimization algorithms) and computing infrastructure (a flexible grid-computing environment).