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Division Spotlight
Accelerator Applications
The division was organized to promote the advancement of knowledge of the use of particle accelerator technologies for nuclear and other applications. It focuses on production of neutrons and other particles, utilization of these particles for scientific or industrial purposes, such as the production or destruction of radionuclides significant to energy, medicine, defense or other endeavors, as well as imaging and diagnostics.
Meeting Spotlight
International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C 2025)
April 27–30, 2025
Denver, CO|The Westin Denver 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
Argonne’s METL gears up to test more sodium fast reactor components
Argonne National Laboratory has successfully swapped out an aging cold trap in the sodium test loop called METL (Mechanisms Engineering Test Loop), the Department of Energy announced April 23. The upgrade is the first of its kind in the United States in more than 30 years, according to the DOE, and will help test components and operations for the sodium-cooled fast reactors being developed now.
Paul Lartaud, Philippe Humbert, and Josselin Garnier
Nuclear Science and Engineering | Volume 197 | Number 8 | August 2023 | Pages 1928-1951
Technical papers from: PHYSOR 2022 | doi.org/10.1080/00295639.2022.2143705
Articles are hosted by Taylor and Francis Online.
In a fissile material, the inherent multiplicity of neutrons born through induced fissions leads to correlations in their detection statistics. The correlations between neutrons can be used to trace back some characteristics of the fissile material. This technique, known as neutron noise analysis, has applications in nuclear safeguards or waste identification. It provides a nondestructive examination method for an unknown fissile material. This is an example of an inverse problem where the cause is inferred from observations of the consequences.
However, neutron correlation measurements are often noisy because of the stochastic nature of the underlying processes. This makes the resolution of the inverse problem more complex since the measurements are strongly dependent on the material characteristics. A minor change in the material properties can lead to very different outputs. Such an inverse problem is said to be ill posed. For an ill-posed inverse problem, the inverse uncertainty quantification is crucial. Indeed, seemingly low noise in the data can lead to strong uncertainties in the estimation of the material properties. Moreover, the analytical framework commonly used to describe neutron correlations relies on strong physical assumptions, and is thus inherently biased.
This paper addresses dual goals. First, surrogate models are used to improve neutron correlation predictions and quantify the errors on those predictions. Then the inverse uncertainty quantification is performed to include the impact of measurement error alongside the residual model bias.