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Division Spotlight
Robotics & Remote Systems
The Mission of the Robotics and Remote Systems Division is to promote the development and application of immersive simulation, robotics, and remote systems for hazardous environments for the purpose of reducing hazardous exposure to individuals, reducing environmental hazards and reducing the cost of performing work.
Meeting Spotlight
ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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 scientists use AI to detect hidden defects in stainless steel
Imagine you’re constructing a bridge or designing an airplane, and everything appears flawless on the outside. However, microscopic flaws beneath the surface could weaken the entire structure over time.
These hidden defects can be difficult to detect with traditional inspection methods, but a new technology developed by scientists at the U.S. Department of Energy’s Argonne National Laboratory is changing that. Using artificial intelligence and advanced imaging techniques, researchers have developed a method to reveal these tiny flaws before they become critical problems.
Yunhuang Zhang, Jean C. Ragusa, Jim E. Morel
Nuclear Science and Engineering | Volume 194 | Number 10 | October 2020 | Pages 903-926
Technical Paper | doi.org/10.1080/00295639.2020.1771141
Articles are hosted by Taylor and Francis Online.
The Simplified () approximation is often used to model radiation transport phenomena, but it converges to the true solution of the transport equation only in one-dimensional slab geometry. In all other geometries, it incurs a model error that needs to be quantified. In this paper, we estimate the radiation transport model error due to the approximation and employ transport solutions (with high order) as reference transport solutions. Because the solution does not contain the full angular information of the transport solution, an angular intensity must be reconstructed from the solution in order to compute the model error. We propose two such reconstruction schemes. Model error estimates are given for various quantities of interests, i.e., scalar radiation intensity, radiation flux, and boundary leakage. An adjoint-based approach is proposed to evaluate the model error and is compared against forward and residual techniques. Two-dimensional numerical experiments are presented.