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Division Spotlight
Thermal Hydraulics
The division provides a forum for focused technical dialogue on thermal hydraulic technology in the nuclear industry. Specifically, this will include heat transfer and fluid mechanics involved in the utilization of nuclear energy. It is intended to attract the highest quality of theoretical and experimental work to ANS, including research on basic phenomena and application to nuclear system design.
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
From South Korea to Belgium: Testing a high-density research reactor fuel
The Korea Atomic Energy Research Institute has developed a high-density uranium silicide fuel designed to replace high-enriched uranium in research reactors. Recent irradiation tests appear to be successful, KAERI reports, which means the fuel could be commercialized to continue a key global nuclear nonproliferation effort—converting research reactors to run on low-enriched uranium fuel.
Hyung Jin Shim, Chang Hyo Kim
Nuclear Science and Engineering | Volume 162 | Number 1 | May 2009 | Pages 98-108
Technical Paper | doi.org/10.13182/NSE09-2
Articles are hosted by Taylor and Francis Online.
The sample variance of a tally in Monte Carlo eigenvalue calculations is biased because of an intercycle correlation between the fission source distributions (FSDs). How to estimate the variance bias or equivalently how to calculate the real variance has been an interesting subject of study. This paper proposes a new method to estimate the real variance based on an intercycle covariance of the FSDs that can be derived from the cycle-by-cycle stochastic error propagation model. The proposed method enables one to calculate every intercycle covariance of a tally accurately, regardless of the number of active cycles. Therefore, the method can be applied satisfactorily even to problems with the dominance ratio (DR) close to 1. The accuracy of the new method is examined for small- and medium-sized pressurized water reactor core problems and a fuel storage facility problem exhibiting a slow source convergence. It is shown that the new method is capable of predicting the variance bias strikingly better than the existing methods, especially for problems with high DRs.