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
Shin‑Yeong Lee (Pohang University of Science and Technology) Hong‑Sang Park (Pohang University of Science and Technology) Jin‑Hwan Kim (Pohang University of Science and Technology) Frédéric Barlat (Pohang University of Science and Technology) Kyung‑Hwan Chung (POSCO)
저널정보
대한금속·재료학회 Metals and Materials International Metals and Materials International Vol.29 No.4
발행연도
2023.4
수록면
892 - 907 (16page)
DOI
10.1007/s12540-022-01268-8

이용수

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

초록· 키워드

오류제보하기
This study investigated the elastic recovery phenomenon with elapsed time and heat treatment after the plastic deformationof automotive steel sheets. A conventional uniaxial loading–unloading-loading test was modified to include the elapsed timeand heat treatment conditions. The elastic behaviors of five automotive steel sheets, MART1500, TRIP1180, EDDQ, DP980,and BH340, were characterized after applying various pre-strains, specific elapsed time conditions, and heat treatments. Theelastic behaviors were quantitatively analyzed using the conventional chord modulus definition and a new elastic modulusdefinition representing the initial elastic characteristics. It was observed that the elastic behavior of BH steel was the mostsensitive to elapsed time and heat treatment in terms of recovery owing to the bake-hardening effect. The elastic moduli of theMART1500 and TRIP1180 steel recovered somewhat after heat treatment, whereas no recoveries of EDDQ and DP980 steelswere observed. Phenomenological modeling of the recovery process was also performed. The Yoshida–Uemori modulusmodel was applied to the experimental results for elastic degradation. This model was then extended to consider the elapsedtime and heat treatment, and the elastic recovery behaviors of the different steels were captured successfully.

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