WAVE FORCE PREDICTION USING AN AUTOREGRESSIVE MODEL

被引:0
|
作者
SAJONIA, CB [1 ]
NIEDZWECKI, JM [1 ]
机构
[1] TEXAS A&M UNIV SYST,DEPT CIVIL ENGN,OCEAN ENGN PROGRAM,COLLEGE STN,TX 77843
关键词
D O I
10.1016/0029-8018(90)90039-9
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
An autoregressive wave force model is developed which is capable of accounting for localized flow history effects. It was developed in conjunction with the analysis of a series of experiments performed to study the wave-induced forces acting on a free-to-surge vertical cylinder in random waves. The wave force model incorporates a relative motion form of the Morison equation. The formulation presented in this study is quite general, but the filter coefficients in the model must be uniquely determined for each data set. The optimal length of the filter and its sensitivity are illustrated using data from small-scale wave tank tests. A high frequency wave force component observed in the experimental data is reproduced using this model. Lastly, the autoregressive wave force model is used to predict the response of a tension-leg platform to a wave train. A comparison of the results obtained both with and without the filter model are presented. © 1990.
引用
收藏
页码:463 / 480
页数:18
相关论文
共 50 条
  • [21] Wave prediction in a port using a fully nonlinear Boussinesq wave model
    Choi, Young-Kwang
    Seo, Seung-Nam
    Choi, Jin-Yong
    Shi, Fengyan
    Park, Kwang-Soon
    ACTA OCEANOLOGICA SINICA, 2019, 38 (07) : 36 - 47
  • [22] Short-term Ocean Wave Forecasting Using an Autoregressive Moving Average Model
    Ge, Ming
    Kerrigan, Eric C.
    2016 UKACC 11TH INTERNATIONAL CONFERENCE ON CONTROL (CONTROL), 2016,
  • [23] Discharge prediction of Amprong river using the ARIMA (autoregressive integrated moving average) model
    Rahayu, Wiwin Sri
    Juwono, Pitojo Tri
    Soetopo, Widandi
    3RD INTERNATIONAL CONFERENCE OF WATER RESOURCES DEVELOPMENT AND ENVIRONMENTAL PROTECTION, 2020, 437
  • [24] Prediction of Mechanical Equipment Vibration Trend Using Autoregressive Integrated Moving Average Model
    Yang, Yanming
    Wu, Weituan
    Sun, Lulu
    2017 10TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI), 2017,
  • [25] Frequency, Damping, and Flutter Prediction from Aircraft Flight Data Using Autoregressive Model
    Sudha, U. P., V
    Deodhare, Girish S.
    Venkatraman, Kartik
    JOURNAL OF AIRCRAFT, 2018, 55 (06): : 2179 - 2190
  • [26] Multivariate arterial travel time prediction using hierarchical subspace vector autoregressive model
    Zhang, Xin, 1600, Sila Science, University Mah Mekan Sok, No 24, Trabzon, Turkey (32):
  • [27] Fuel cell performance prediction using an AutoRegressive Moving-Average ARMA model
    Detti, A. H.
    Yousfi-Steiner, N.
    Bouillaut, L.
    Same, A. B.
    Jemei, S.
    2019 IEEE VEHICLE POWER AND PROPULSION CONFERENCE (VPPC), 2019,
  • [28] Significant wave height prediction by using a spatial model
    Altunkaynak, A
    OCEAN ENGINEERING, 2005, 32 (8-9) : 924 - 936
  • [29] Wave Prediction Using Genetic Programming and Model Trees
    Rambekar, A. R.
    Deo, M. C.
    JOURNAL OF COASTAL RESEARCH, 2012, 28 (01) : 43 - 50
  • [30] Separated Model for Stopping Point Prediction of Autoregressive Sequence
    Liu, Tingzhen
    Zhang, Shengxi
    Xiong, Qianqian
    2023 IEEE 12TH DATA DRIVEN CONTROL AND LEARNING SYSTEMS CONFERENCE, DDCLS, 2023, : 799 - 803