Current Model Analysis of South China Sea Based on Empirical Orthogonal Function(EOF) Decomposition and Prototype Monitoring Data

被引:0
|
作者
WU Wenhua [1 ,2 ]
LIU Ming [1 ]
YU Siyuan [1 ]
WANG Yanlin [3 ]
机构
[1] Department of Engineering Mechanics, Faculty of Vehicle and Mechanics, Dalian University of Technology
[2] State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology
[3] School of Ocean Science and Technology, Dalian University of Technology
基金
中国国家自然科学基金;
关键词
current profile model; failure criteria; prototype monitoring; inverse first-order reliability method(IFORM); Characteristic profile current(CPC);
D O I
暂无
中图分类号
P714 [调查及观测方法];
学科分类号
0816 ;
摘要
Environmental load is the primary factor in the design of offshore engineering structures and ocean current is the principal environmental load that causes underwater structural failure. In computational analysis, the calculation of current load is mainly based on the current profile. The current profile model, which is based on a structural failure criterion, is conducive to decreasing the uncertainty of the current load. In this study, we used prototype monitoring data and the empirical orthogonal function(EOF) method to investigate the current profile in the South China Sea and its correlation with the design of underwater structural strength and the dynamic design of fatigue. The underwater structural strength design takes into account the size of the structure and the service water depth. We propose profiles for the overall and local designs using the inverse first-order reliability method(IFORM). We extracted the characteristic profile current(CPC) of the monitored sea area to solve dynamic design problems such as vortex-induced vibration(VIV). We used random sampling to verify the feasibility of using the EOF method to calculate the CPC from the current data and identified the main problems associated with using the CPC, which deserve close attention in VIV design. Our research conclusions provide direct references for determining current load in this sea area. This analysis method can also be used in the analysis of other sea areas or field variables.
引用
收藏
页码:305 / 316
页数:12
相关论文
共 50 条
  • [1] Current Model Analysis of South China Sea Based on Empirical Orthogonal Function (EOF) Decomposition and Prototype Monitoring Data
    Wenhua Wu
    Ming Liu
    Siyuan Yu
    Yanlin Wang
    Journal of Ocean University of China, 2019, 18 : 305 - 316
  • [2] Current Model Analysis of South China Sea Based on Empirical Orthogonal Function (EOF) Decomposition and Prototype Monitoring Data
    Wu, Wenhua
    Liu, Ming
    Yu, Siyuan
    Wang, Yanlin
    JOURNAL OF OCEAN UNIVERSITY OF CHINA, 2019, 18 (02) : 305 - 316
  • [3] Analysis of the regional spectral properties in northwestern South China Sea based on an empirical orthogonal function
    Fu, Dongyang
    Huang, Yuye
    Liu, Dazhao
    Liao, Shan
    Yu, Guo
    Zhang, Xiaolong
    ACTA OCEANOLOGICA SINICA, 2020, 39 (07) : 107 - 114
  • [4] Analysis of the regional spectral properties in northwestern South China Sea based on an empirical orthogonal function
    Dongyang Fu
    Yuye Huang
    Dazhao Liu
    Shan Liao
    Guo Yu
    Xiaolong Zhang
    Acta Oceanologica Sinica, 2020, 39 : 107 - 114
  • [5] Analysis of the regional spectral properties in northwestern South China Sea based on an empirical orthogonal function
    Dongyang Fu
    Yuye Huang
    Dazhao Liu
    Shan Liao
    Guo Yu
    Xiaolong Zhang
    Acta Oceanologica Sinica, 2020, 39 (07) : 107 - 114
  • [6] SIGNIFICANCE TEST FOR EMPIRICAL ORTHOGONAL FUNCTION (EOF) ANALYSIS OF METEOROLOGICAL AND OCEANIC DATA
    李晓峰
    Pietrafesa
    L.J
    蓝淑芳
    谢立安
    ChineseJournalofOceanologyandLimnology, 2000, (01) : 10 - 17
  • [7] Design-based empirical orthogonal function model for environmental monitoring data analysis
    Munoz, Breda
    Lesser, Virginia M.
    Ramsey, Fred L.
    ENVIRONMETRICS, 2008, 19 (08) : 805 - 817
  • [8] Significance test for empirical orthogonal function (EOF) analysis of meteorological and oceanic data
    Li Xiao-feng
    L. Pietrafesa
    Lan Shu-fang
    Xie Li-an
    Chinese Journal of Oceanology and Limnology, 2000, 18 (1): : 10 - 17
  • [9] Empirical Orthogonal Function (EOF) analysis of sea-surface temperature and chlorophyll in the eastern Bering Sea
    Naik, Puneeta
    D'Sa, Eurico J.
    REMOTE SENSING OF THE OCEAN, SEA ICE, AND LARGE WATER REGIONS 2010, 2010, 7825
  • [10] Temporal and spatial variability of chlorophyll concentrations in the Bering Sea using empirical orthogonal function (EOF) analysis of remote sensing data
    Iida, Takahiro
    Saitoh, Sei-Ichi
    DEEP-SEA RESEARCH PART II-TOPICAL STUDIES IN OCEANOGRAPHY, 2007, 54 (23-26) : 2657 - 2671