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
Kumara, Janaka J. (Department of Civil Engineering, Tokyo University of Science) Hayano, Kimitoshi (Department of Urban Innovation, Yokohama National University)
저널정보
테크노프레스 Geomechanics & engineering Geomechanics & engineering 제10권 제4호
발행연도
2016.1
수록면
455 - 470 (16page)

이용수

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

초록· 키워드

오류제보하기
In ballasted railway tracks, ballast fouling due to finer material intrusion has been identified as a challenging issue in track maintenance works. In this research, deformation characteristics of crushed stone-sand mixtures, simulating fresh and fouled ballasts were studied from laboratory and a 3-D discrete element method (DEM) triaxial compression tests. The DEM simulation was performed using a recently developed DEM approach, named, Yet Another Dynamic Engine (YADE). First, void ratio characteristics of crushed stone-sand mixtures were studied. Then, triaxial compression tests were conducted on specimens with 80 and 50% of relative densities simulating dense and loose states respectively. Initial DEM simulations were conducted using sphere particles. As stress-strain behaviour of crushed stone-sand mixtures evaluated by sphere particles were different from laboratory specimens, in next DEM simulations, the particles were modeled by a clump particle. The clump shape was selected using shape indexes of the actual particles evaluated by an image analysis. It was observed that the packing behaviour of laboratory crushed stone-sand mixtures were matched well with the DEM simulation with clump particles. The results also showed that the strength properties of crushed stone deteriorate when they are mixed by 30% or more of sand, specially under dense state. The results also showed that clump particles give closer stress-strain behaviour to laboratory specimens than sphere particles.

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