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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
Conference on Nuclear Training and Education: A Biennial International Forum (CONTE 2025)
February 3–6, 2025
Amelia Island, FL|Omni Amelia Island Resort
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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Biden executive order to facilitate AI data center power
As demand for artificial intelligence and data centers grows, President Biden issued an executive order yesterday aimed to ensure clean-energy power supply for the technology.
Paul Wilson, Phiphat Phruksarojanakun
Nuclear Science and Engineering | Volume 152 | Number 3 | March 2006 | Pages 243-255
Technical Paper | doi.org/10.13182/NSE06-A2579
Articles are hosted by Taylor and Francis Online.
A new Monte Carlo (MC) method for calculating the isotopic inventory of material subjected to a neutron flux is developed and demonstrated. The method is particularly suited to modeling materials that flow through a system in a nondeterministic path. The method has strong analogies to MC neutral particle transport. The analog methodology is fully developed, including considerations for simple, complex, and loop flows, and enabling concepts such as sources and tallies. A wide variety of test problems is employed to demonstrate the validity of the analog method under various flow conditions. The method reproduced the results of the as-low-as-reasonably-achievable deterministic inventory code for comparable problems and is self-consistent when comparing complex flow scenarios to mathematically identical simple flow scenarios. A demonstration of highly scalable parallelization does not eliminate the need to develop variance reduction techniques.