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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.
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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
Securing the advanced reactor fleet
Physical protection accounts for a significant portion of a nuclear power plant’s operational costs. As the U.S. moves toward smaller and safer advanced reactors, similar protection strategies could prove cost prohibitive. For tomorrow’s small modular reactors and microreactors, security costs must remain appropriate to the size of the reactor for economical operation.
Seyed Mohsen Hoseyni, Mohammad Pourgol-Mohammad
Nuclear Technology | Volume 193 | Number 3 | March 2016 | Pages 341-363
Technical Paper | doi.org/10.13182/NT15-47
Articles are hosted by Taylor and Francis Online.
The influence of model uncertainty is most pronounced in areas of limited knowledge and large uncertainties like severe accident (SA) calculations. Lack of a systematic methodology for this purpose makes this assessment difficult. This paper describes the treatment of model uncertainty in SA analysis for nuclear power plants, which is an area that has had limited past research. This paper aims at a systematic subject assessment. By review of available approaches, a methodology is structured to deal with alternative modeling options in SA code structure. The proposed methodology comprises three phases: the probability of each model is estimated (phase 1), the input uncertainty is quantified (phase 2), and the Bayesian model averaging technique is utilized to integrate the calculations of alternative models into the SA code (phase 3). Through this process, the degree of belief is quantified for the performance of alternative code models. The methodology evaluates available information and data from experiments and code predictions. The application of the proposed methodology is demonstrated on fission product release models for the LP-FP-2 SA experiment of the LOFT (Loss-of-Fluid Test) facility.