ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
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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
2025 ANS Annual Conference
June 15–18, 2025
Chicago, IL|Chicago Marriott Downtown
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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June 2025
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Latest News
Countering the nuclear workforce shortage narrative
James Chamberlain, director of the Nuclear, Utilities, and Energy Sector at Rullion, has declared that the nuclear industry will not have workforce challenges going forward. “It’s time to challenge the scarcity narrative,” he wrote in a recent online article. “Nuclear isn't short of talent; it’s short of imagination in how it attracts, trains, and supports the workforce of the future.”
O. J. Wallace
Nuclear Science and Engineering | Volume 78 | Number 1 | May 1981 | Pages 78-85
Technical Note | doi.org/10.13182/NSE81-A19609
Articles are hosted by Taylor and Francis Online.
Calculations based on the integration of the point kernel over a finite source region are widely used in obtaining gamma-ray fluxes, dose rates, and heating rates. For most cases of practical interest, this integration must be done numerically. The relative merits of the trapezoidal rule, Gauss quadrature, and the semi-Gauss automatic quadrature algorithm of Patterson are discussed as they apply to the integration of the point kernel. The Patterson algorithm is superior to other quadrature algorithms for this application because it allows results to be calculated to a predetermined relative error, wastes no function evaluations, is accurate, and supplies relative error data along with the answer. It is efficient with respect to both engineering and computer time. The implementation of this algorithm for point-kernel integrations is described in detail.