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 Coastal cliffs are continuously shaped by forces from waves, tides, and storm surges, leading to significant erosion and structural changes that affect both natural and built environments. Understanding how fluid dynamics, soil behaviour, and foundation performance interact is essential for resilient coastal infrastructure and sustainable land-use planning. This study introduces a new conceptual and numerical modelling framework, the Fluid-Cliff-Foundation Interaction (FCFI) model, which provides a structured approach to analysing the dynamics between hydrodynamic forces, cliff morphology, soil properties, and foundation stability. Using a location-specific case study in Sidmouth, UK, the FCFI framework is applied through numerical simulations to evaluate the performance of foundations placed at varying distances from the cliff edge. The study focuses on two foundation configurations, those located close to the cliff crest and those farther. The modelling results show that foundations within 12 m of the cliff crest experience significantly higher deformation and instability under wave loading, indicating a critical risk zone. It is also shown that foundations on hard soil enhance stability and reduce deformation in bearing structure-soil-structure interaction. These results underscore the importance of considering soil type and proximity to the cliff in the analysis and placement of coastal infrastructure. This work contributes a novel integrative methodology combining geotechnical modelling and coastal dynamics, offering a basis for identifying vulnerable zones along cliff crests where wave action has a significant impact. These insights are valuable for site-specific infrastructure planning and for informing broader coastal management strategies aimed at balancing development with environmental risk mitigation.
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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