Original Article
  • Prediction of Stacking Angles of Fiber-reinforced Composite Materials Using Deep Learning Based on Convolutional Neural Networks

  • Hyunsoo Hong*, Wonki Kim*, Doyun Jeon*, Kwanho Lee**, Seong Su Kim*†

  • * Department of Mechanical Engineering, KAIST
    ** Hyundai Motor Company

  • 합성곱 신경망 기반의 딥러닝을 이용한 섬유 강화 복합재료의 적층 각도 예측

  • 홍현수*· 김원기*· 전도윤*· 이관호**· 김성수*†

  • This article is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

References
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  • 2. Jeong, K.I., Kim, W., Jeong, J.M., Oh, J., Bang, Y.H., and Kim, S.S., “A Study on the Application of Carbon Fiber Reinforced Plastics to PTO Shafts for Aircrafts,” Composites Research, Vol. 34, No. 6, 2021, pp. 380-386.
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  • 3. Hong, H., Sarfraz, M.S., Jeong, M., Kim, T., Choi, J., Kong, K., Park, I., and Kim, S.S., “Prediction of Ground Reaction Forces Using the Artificial Neural Network from Capacitive Self-sensing Values of Composite Ankle Springs for Exo-robots,” Composite Structures, Vol. 301, 2022, p. 116233.
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  • 4. Sarfraz, M.S., Hong, H., and Kim, S.S., “Recent Developments in the Manufacturing Technologies of Composite Components and Their Cost-effectiveness in the Automotive Industry: A Review Study,” Composite Structures, Vol. 266, 2021, p. 113864.
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  • 6. Sharp, N.D., Goodsell, J.E., and Favaloro, A.J., “Measuring Fiber Orientation of Elliptical Fibers from Optical Microscopy,” Journal of Composites Science, Vol. 3, No. 1, 2019, p. 23.
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  • 8. Bhaduri, A., Gupta, A., and Graham-Brady, L., “Stress Field Prediction in Fiber-reinforced Composite Materials Using a Deep Learning Approach,” Composites Part B: Engineering, Vol. 238, 2022, p. 109879.
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  • 9. Sengodan, G.A., “Prediction of Two-phase Composite Microstructure Properties Through Deep Learning of Reduced Dimensional Structure-response Data,” Composites Part B: Engineering, Vol. 225, 2021, p. 109282.
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  • 10. Caglar, B., Broggi, G., Ali, M.A., Orgéas, L., and Michaud, V., “Deep Learning Accelerated Prediction of the Permeability of Fibrous Microstructures,” Composites Part A: Applied Science and Manufacturing, Vol. 158, 2022, p. 106973.
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This Article

Correspondence to

  • Seong Su Kim

  • Department of Mechanical Engineering, KAIST

  • E-mail: seongsukim@kaist.ac.kr