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Prediction of the Mechanical behavior of Short-Fiber Reinforced Composite Structures using Compression Molding-Structural Coupled Analysis

압축 성형-구조 연계 해석을 활용한 단섬유 강화 복합소재 구조물의 기계적 거동 예측

  • Da-Young Jang (Department of Mechanical Engineering, Kumoh National Institute of Technology) ;
  • Geung-Hyeon Lee (Department of Mechanical Engineering, Kumoh National Institute of Technology) ;
  • Jang-Woo Han (School of Mechanical System Engineering, Kumoh National Institute of Technology)
  • 장다영 (국립금오공과대학교 기계공학과 ) ;
  • 이긍현 (국립금오공과대학교 기계공학과 ) ;
  • 한장우 (국립금오공과대학교 기계시스템공학부)
  • Received : 2024.06.24
  • Accepted : 2024.08.16
  • Published : 2024.10.31

Abstract

In this paper, compression molding-structural coupled analysis was proposed to accurately consider the effect of initial compression molding conditions on the mechanical behavior of short-fiber reinforced composite structures. To this end, local short-fiber orientations depending on the initial charge conditions were investigated using compression molding analysis, and a mean-field homogenization scheme was employed to efficiently derive equivalent orthotropic material properties determined by short-fiber orientations. Furthermore, based on the refined finite element model with short-fiber orientation, compression molding-structural coupled analysis precisely described the locally independent mechanical behavior induced by initial molding conditions. Consequently, it could be confirmed that the proposed analysis model provides a reasonable solution in the design process of short-fiber reinforced composite structures manufactured by compression molding.

본 논문에서는 초기 압축 성형 공정 조건들이 단섬유 강화 복합소재 구조물의 기계적 거동 특성에 미치는 영향을 효과적으로 반영할 수 있는 압축 성형-구조 연계 해석 방안을 제안하였다. 압축 성형 해석을 바탕으로 초기 charge의 형상 및 배치에 따른 부위별 단섬유 배향 특성을 분석하였으며, 평균장 균질화 이론을 통해 단섬유 배향 특성에 따른 등가 이방 물성을 도출하였다. 나아가, 단섬유 배향 정보가 Mapping된 유한요소 모델을 기반으로 초기 공정 조건들에 의해 야기되는 부위별 거동 특성 변화를 고려할 수 있는 압축 성형-구조 연계 해석을 진행하였다. 관련 수치 예제 검증을 통해 제시된 해석 방안은 압축 성형을 통해 제작된 단섬유 강화 복합소재 구조물 설계 과정에서 효과적인 솔루션을 제공함을 확인하였다.

Keywords

Acknowledgement

이 성과는 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구이며(NRF-2022R1C1C1012599), 또한 중소벤처기업부에서 지원하는 2022년도 맞춤형 기술파트너 지원사업(RS-2022-00155265)의 연구수행으로 인한 결과물임.

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