Science of Emotion and Sensibility (감성과학)

Korean Society for Emotion and Sensibility (한국감성과학회)
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A Study on the Possibility of Using Fire-Retardant Working Cloth Made from Silicon Carbide (SiC) Composite Spun Yarns

Silicon Carbide (SiC) 복합방적사로부터 제조된 원단의 방화복 활용 가능성에 관한 연구

  • Received : 2021.01.04
  • Accepted : 2021.11.19
  • Published : 2021.12.31
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Abstract

The mechanical properties of a woven fabric made of SiC (silicon carbide) fibers were determined in this study using the KES-FB system. The woven fabric is used in high heat settings above 1500℃. Composite spun yarns were used to create SiC fibers. By analyzing the wearing properties, we studied the prospect of using the textiles as fire-retardant work clothes. Mechanical properties determine the wearing attributes. Therefore, the tensile linearity (LT), tensile resilience (RT), and shear stiffness (G) values of the fabric varied according to the yarn type (filament or spun yarn). The thickness, weight per square meter, and density of the fabric were found to have an effect on the shear hysteresis (2HG) and compression resilience (RC) values. In terms of wearable clothing qualities, the fabric qualities of the SiC composite yarn demonstrated the highest ratio of compressive energy to thickness (WC/T), which indicates bulkiness. The fabric manufactured from SiC composite yarns passed the KFI criteria for carbonation length and cumulative flame time in the flame-retardant test. Therefore, we discovered that the material can be used as a fire-resistant work cloth.

본 연구에서는 1500℃ 이상의 극한 열 환경에서 사용되는 소재인 SiC (silicon carbide) 섬유를 복합방적사로 제조한 후에 원단을 제직하고 제직된 원단의 역학적 특성을 KES-FB system으로 측정하고 측정된 역학적 특성 값으로부터 착용성능을 분석하여 방화복으로의 활용 가능성을 알아보았다. 그 결과 직물의 역학적 특성에서는 인장선형성(LT)과 인장레질리언스(RT), 전단강성(G)을 나타내는 값이 원사의 제조형태에 따라서 그 특성 값의 차이를 보였으며, 직물의 두께와 평량, 밀도 값이 전단히스테리시스(2HG)와 압축레질리언스(RC) 값에 영향을 준다는 것을 알 수 있었다. 의복착용 성능에서는 착용 시 부피감을 나타내는 두께에 대한 압축에너지의 비(WC/T) 값에서 SiC 복합방적사로 제조된 직물의 값이 가장 우수한 값을 타나내었으며, 방염성능에서는 SiC 복합방적사로 제조된 직물이 탄화길이와 잔염시간에서 KFI 성능기준을 만족하여 방화복으로서의 활용이 가능함을 확인할 수 있었다.

Keywords

Acknowledgement

이 논문은 2019년도 산업통상자원부 및 산업기술평가관리원(KEIT) 연구비 지원에 의한 연구임('20003890').

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