인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Abstract Ensuring high-quality fill compaction is crucial for the stability and longevity of infrastructures and affects the sustainability of urban infrastructure networks. The purpose of this paper is to provide a refined analysis and insight understanding of the current practice, limitations, challenges, and future development trends of compaction methods from the perspective of the development stage. This paper offers a comprehensive overview of the evolution of compaction methods and classifies compaction quality control methods into four groups through quantitative analysis of literature: traditional compaction methods, digital compaction methods, automated compaction methods, and intelligent compaction methods. Each method's properties and issues are succinctly stated. Then, the research on three key issues in intelligent compaction including compaction quality evaluation algorithms, dynamic optimal path planning, and implementation of unmanned technology is summarized. Currently, the field of intelligent compaction is far from mature, a few challenges and limitations need further investigation: coupling problems of multiple indicators in intelligent evaluation algorithms, unmanned roller groups collaborative control problems, and intelligent decision-making and optimization problems of multi-vehicle compaction paths. This review serves as a valuable reference for systematically understanding the development of compaction methods.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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