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3D 프린팅용 SHCC의 흐름값과 1축 인장 특성에 미치는 섬유 혼입률의 영향

Effect of Fiber Volume Fractions on Flow and Uniaxial Tension Properties of 3D Printed SHCC

  • 현창진 (충남대학교 토목공학과) ;
  • 김효정 (충남대학교 스마트인프라건설연구소) ;
  • 이병재 (대전대학교 토목환경공학과) ;
  • 김윤용 (충남대학교 토목공학과)
  • 투고 : 2024.05.24
  • 심사 : 2024.06.14
  • 발행 : 2024.06.30

초록

이 연구는 PVA 섬유로 보강된 변형경화형 시멘트 복합재료(SHCC)의 3D 프린팅 특성을 조사하였다. 섬유 혼입률(Vf)의 영향을 파악하기 위하여 섬유 혼입률이 다른 F1.0 (Vf=1.0%), F1.5 (Vf=1.5%), F1.8 (Vf=1.0%) 등의 3가지 SHCC 배합을 제작하였다. F1.5와 F1.8 배합이 다중 미세균열 발생을 위한 이론적 필수 조건을 충족하는 것으로 나타났으며, 섬유 혼입률이 높을수록 필수 조건은 더 쉽게 충족되었다. 3가지 SHCC 배합의 흐름값은 120~160의 범위 내에 있어 3D 프린팅 가능한 범주에 있음을 확인하였다. 한편, 섬유 혼입률이 증가할수록 흐름값은 감소하였다. 3D 프린터로 출력된 SHCC 표면의 육안 관찰 결과, F1.0 혼합물은 Level-3 등급으로, F1.5와 F1.8 혼합물은 Level-2 등급으로 평가되었다. 섬유 혼입률이 높을수록 표면 품질이 저하 되어, 추후 연구를 통하여 보다 높은 품질의 3D 프린팅용 SHCC를 제작하기 위한 배합 조정이 필요할 것으로 사료된다. 1축 인장 거동을 살펴본 결과, F1.0 혼합물은 낮은 변형률에서 파괴된 반면, F1.5와 F1.8 혼합물은 다중 미세균열이 발생하면서 우수한 인장변형률 경화거동을 나타내었다.

This study investigates the 3D printing characteristics of strain hardening cement composites (SHCC) reinforced by PVA fibers. Three SHCC mixtures with diverse fiber volume fractions (1.0% for F1.0 mixture, 1.5% for F1.5 mixture, and 1.8% for F1.8 mixture) were designed. Except for the F1.0 mixture, all mixtures met the necessary conditions for multiple micro-cracking, with higher fiber volume fractions more readily satisfying these conditions. The flow values of three SHCC mixtures were within the 3D printable range of 120~160 mm, exhibiting decreased flow values with increasing the fiber volume fractions. Observation of the printed SHCC surfaces indicated that the F1.0 mixture had a Level-3 (good) rating, while F1.5 and F1.8 were rated as Level-2 (average). Higher fiber volume fractions resulted in poorer surface quality, thus, further research needs to be performed for modulating SHCC mixture suitable for 3D printing. The uniaxial tension behavior showed that the F1.0 mixture failed at lower strain, whereas F1.5 and F1.8 exhibited higher strain performance with multiple micro-cracks occurring.

키워드

과제정보

이 논문은 2020년도 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 기초연구사업임(NRF-2020R1A2C1101465).

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