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Los Alamos National Laboratory-Jeonbuk National University Engineering Institute-Korea Transfers Non-Destructive Testing Know-How

  • 전북대학교
  • 2021-12-01
  • 조회수 53
 게시글 썸네일

Los Alamos National Laboratory-Jeonbuk National University Engineering Institute-Korea (Director Kang Rae-hyung, Professor, Department of Flexible Printed Electronics) announced on the 29th that it recently signed a Technology Transfer agreement worth KRW 110 million with a domestic non-destructive testing company.


The technology transferred this time is the institute's in-house developed "defect image visualization technology know-how for non-destructive inspection of heat-resistant composite materials."


This technology is a state-of-the-art method that can identify internal interlaminar delamination defects in heat-resistant composite materials, which are not inspectable by conventional X-ray or other inspection techniques.


Prior to the development of this technology, only inefficient, uneconomical, and unsafe testing methods existed, such as repeatedly testing aerospace and defense airframes that use heat-resistant composite materials or disassembling completed structures to examine adhesion.


Director Kang said, "Based on the institute's world-class non-destructive testing technology, we have, for the first time in the world, been able to confirm internal interlaminar delamination defects in these heat-resistant composite materials," and added, "This technology can be usefully applied to the national aerospace and defense industries and is expected to expand to other industries as well."


Meanwhile, Los Alamos National Laboratory-Jeonbuk National University Engineering Institute-Korea is developing convergence technologies that integrate diverse fields such as mechanical engineering, electronics, carbon materials and smart materials, flexible printed electronic devices, and 3D printing. The institute possesses cutting-edge non-destructive testing technologies as well as smart sensor technologies, materials technologies for composites, signal processing and control technologies, and deep learning-based data analysis capabilities, and conducts world-class research in the field of structural health management.



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