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Division Spotlight
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.
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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Latest News
BREAKING NEWS: Trump issues executive orders to overhaul nuclear industry
The Trump administration issued four executive orders today aimed at boosting domestic nuclear deployment ahead of significant growth in projected energy demand in the coming decades.
During a live signing in the Oval Office, President Donald Trump called nuclear “a hot industry,” adding, “It’s a brilliant industry. [But] you’ve got to do it right. It’s become very safe and environmental.”
T. Kawano, K. M. Hanson, S. Frankle, P. Talou, M. B. Chadwick, R. C. Little
Nuclear Science and Engineering | Volume 153 | Number 1 | May 2006 | Pages 1-7
Technical Paper | doi.org/10.13182/NSE06-A2589
Articles are hosted by Taylor and Francis Online.
We present an approach to uncertainty quantification for nuclear applications that combines the covariance evaluation of differential cross-section data and the error propagation from matching a criticality experiment using a neutron-transport calculation. We have studied the reduction in uncertainty of 239Pu fission cross sections by using a one-dimensional neutron-transport calculation with the PARTISN code. The evaluation of 239Pu differential cross-section data is combined with a criticality measurement (Jezebel) using a Bayesian method. To quantify the uncertainty in such calculations, we generate a set of random samples of the cross sections, which represents the covariance matrix, and estimate the distribution of calculated quantities, such as criticality. We show that inclusion of the Jezebel data reduces uncertainties in estimating neutron multiplicity.