Local Scour Mechanisms and Prediction Methods Around Offshore Wind Turbine Foundations: Insights and Future Directions

被引:0
|
作者
Yang, Qi [1 ]
Hu, Ruigeng [2 ]
Yu, Peng [3 ]
Zhang, Peng [4 ]
Xu, Zhongqian [5 ]
Xu, Mengzhen [1 ]
机构
[1] Tsinghua Univ, State Key Lab Hydrosci & Engn, Beijing 100084, Peoples R China
[2] Sinopec Petr Engn Corp, Dongying 257100, Peoples R China
[3] Qingdao Geoengn Surveying Inst, Minist Nat Resources, Key Lab Geol Safety Coastal Urban Underground Spac, Qingdao 266101, Peoples R China
[4] Qingdao Qingzi Engn Consulting Co Ltd, Qingdao 266061, Peoples R China
[5] Qingdao Water Affairs Dev Serv Ctr, Qingdao 266033, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
local scour; offshore wind turbine foundations; wave-current actions; sediment transport; multiscale vortices; numerical modeling; COMBINED WAVES; CLEAR-WATER; NUMERICAL-SIMULATION; TIME DEVELOPMENT; BRIDGE PIER; PILE; MONOPILE; PROTECTION; TURBULENCE; DEPTH;
D O I
10.1007/s11802-024-5957-6
中图分类号
P7 [海洋学];
学科分类号
0707 ;
摘要
Local scour around offshore wind turbine foundations presents a considerable challenge due to its potential influence on structural stability, driven by hydrodynamic forces. While research has made strides in comprehending scouring mechanisms, notable complexities persist, specifically with newer foundation types. Addressing these limitations is vital for advancing our understanding of scour mechanisms and for improving mitigation strategies in offshore wind energy development. This review synthesizes current findings on local scour across various offshore foundations, encompassing field observations, data-driven approaches, turbulence-sediment interactions, scour evolution processes, influencing factors, and numerical model advancements. The objective is to enrich our understanding of local scour mechanisms. In addition, future research directions are outlined, including the development of robust artificial intelligence models for accurate predictions, the exploration of vortex structure characteristics, and the refinement of numerical models to strengthen prediction capabilities while minimizing computational efforts.
引用
收藏
页码:1248 / 1262
页数:15
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