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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.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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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Become a knowledge manager at UWC 2024
The American Nuclear Society is now accepting applications for knowledge managers to work during the 2024 Utility Working Conference and Vendor Technology Expo. This year’s UWC, “Nuclear Momentum: Advancing Our Clean Energy Future,” will be held August 4–7, 2024, at the JW Marriott Marco Island Beach Resort on Marco Island, Fla.=
Matthew Quinn, David Orozco, Kurt Boehm, Brian Sammuli, Wendi Sweet
Fusion Science and Technology | Volume 79 | Number 7 | October 2023 | Pages 791-800
Research Article | doi.org/10.1080/15361055.2023.2204201
Articles are hosted by Taylor and Francis Online.
The success of inertial confinement fusion experiments hinges on the production of perfectly round spherical capsules placed at the center of an implosion. Some of the most common ablator materials are grown on poly(alpha-methylstyrene) (PAMS) mandrels. Human operator–based optical inspection of individual PAMS mandrels followed by a selection decision, is a labor-intensive process that suffers from operator dependence. General Atomics has developed a robotic system to handle and image these delicate PAMS mandrels and has implemented an autonomous method for evaluating shell quality. The selection criteria of acceptable mandrels has been standardized by employing visual defect characterization tools and associated machine learning algorithms. This work discusses the mechanical upgrades made to the robot cell for handling shells, the suite of software tools developed for a more complete evaluation of individual shells, and correlating defect statistics from entire batches to production data from the PAMS fabrication process parameters.