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Division Spotlight
Decommissioning & Environmental Sciences
The mission of the Decommissioning and Environmental Sciences (DES) Division is to promote the development and use of those skills and technologies associated with the use of nuclear energy and the optimal management and stewardship of the environment, sustainable development, decommissioning, remediation, reutilization, and long-term surveillance and maintenance of nuclear-related installations, and sites. The target audience for this effort is the membership of the Division, the Society, and the public at large.
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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Latest News
DOE-EM awards $37.5M to Vanderbilt University for nuclear cleanup support
The Department of Energy’s Office of Environmental Management announced on January 16 that it has awarded a noncompetitive financial assistance agreement worth $37.5 million to Vanderbilt University in Nashville, Tenn., to aid the department’s mission of cleaning up legacy nuclear waste.
A. C. Nelson, JR., W. S. Minkler
Nuclear Science and Engineering | Volume 17 | Number 1 | September 1963 | Pages 101-110
Technical Paper | doi.org/10.13182/NSE63-A17215
Articles are hosted by Taylor and Francis Online.
A general method has been developed for evaluating the effects of uncertainties in design variables on the ability of a core to meet various transient and steady-state limiting thermal criteria. The performance characteristics of interest are evaluated by digital computer at carefully selected points in the parameter regions of interest, and the results are fitted by least squares to a polynomial approximation. Statistical information and/or limiting values may be readily applied to this approximation to yield a bound on the probability that the thermal design limits will not be exceeded.
