메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색

논문 기본 정보

자료유형
학술저널
저자정보
김영리 (서울대학교 의류학과 박사후과정 연구원)
저널정보
한국의류학회 한국의류학회지 한국의류학회지 제21권 제1호
발행연도
1997.1
수록면
170 - 181 (12page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색

초록· 키워드

오류제보하기
The purpose of this study was to determine the effect of knit structure and knit density (machine tightness factor) on the dimensional properties and K1-4 values of weft-knitted fabrics followed over eleven cycles of mechanical relaxation to provide the basic data for constructing weft-knitted fabrics for outwear with excellent dimensional stability The eighteenth weft-knitted fabrics were produced with different knit structure (1$\times$1 rib, half-cardigan rib, half-milano rib, interlock, single pique, crossmiss interlock) and machine tightness factor (loose, medium, tight) for this study. Dimensional properties such as width, lengh, area shrinkage and dimensional parameter (K) of eighteenth knitted fabrics including thickness and bulk property were measured. The results were as follows; 1. The dimensional behavior of the Ix1 rib and interlock in relaxation cycles was anisotropic, i.e., length shrinkage was usually associated with a width expansion, whereas the other weft-kntted fabrics which have tuck or miss loops in the knit structure behaved isotropically, i.e., length and width shrinkages were usually found. It was proposed that the difference in dimensional behavior between these structures was due to the dissimilar nonrelaxed geometrical shapes of the individual structural units forming these weft-knitted structures. The mechanical relaxation shrinkage of weft-knitted cotton fabrics was dependent on the tightness of construction. For a range of fabrics knitted on this study, an increase in fabric tightness caused a decrease in the length shrinkage of the fabric accompanied by an increase in its width shrinkage.

목차

등록된 정보가 없습니다.

참고문헌 (0)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0