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本文基于中国首套长时间序列、高精度、高时空一致性的全球海洋气候数据集产品, 利用1993年1月至2015年12月的山东半岛近海海平面异常数据, 构建了基于集合经验模式分解(EEMD)和长短期记忆神经网络(LSTM)的海平面非线性变化组合预测模型。EEMD可以得到海平面异常的各周期项、线性趋势及残差部分, LSTM模型可对其进行逐个预测并重构得到最终的海平面异常预测结果。EEMD-LSTM组合模型海平面异常预测的均方根误差仅为25.87 mm, 取得了令人满意的效果。基于该组合模型预测2016-2025年山东半岛近海海平面上升速率将达到3.54 mm·a-1。 相似文献
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近海区域广泛分布着第四纪新沉积的松散海洋土,波浪荷载作用下松散海床会发生液化进而对近海结构物的稳定性存在巨大威胁。本文采用中国科学院流体-结构-海床相互作用数值计算模型FSSI-CAS 2D,选用Pastor-Zienkiewicz-Mark Ⅲ（PZⅢ）弹塑性本构研究了波浪诱发的松散海床液化问题。分析了波浪荷载引起的松散海床内超孔隙水压力、有效应力以及应力角的时程变化特性,并预测了松散海床的渐进液化过程。计算结果表明,波浪荷载作用下松散海床内残余孔压会累积增长,海床表面最先发生液化,然后逐渐向下发展至液化最大深度。同时指出海床内超孔隙水压力的竖向分布特征和应力角的变化时程均可以作为判断海床液化的间接参数。最后,通过应力状态分析,讨论了海床渐进式液化的发展过程和趋势。 相似文献
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台湾岛地处亚欧大陆和太平洋交界处,台风、东北季风等所引起的海洋灾害频繁,所以建立完备的海洋水文观测体系显得尤为重要.中国台湾自主建置完成的近海水文观测体系由资料浮标站、观测桩、潮位站、岸边气象站、雷达测波站等多种近海水文观测系统构建组成;同时,为确保观测体系的准确性和规范性,还建立了数据品质管理系统和标准化作业模式.在近海水文观测数据的分析方面,尝试应用新的数学分析方法,如通过EMD(empirical mode decomposition)方法探讨风暴潮水位变化,利用小波转换从雷达观测影像中分析近岸波浪信息,以及发展数据同化技术将观测数据应用于作业化波浪现报、预报模式.此外,近海水文观测体系在社会应用方面有着很大的发展潜质. 相似文献
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利用高分辨率的大气和波浪数值模式,模拟了2016年苏北近海的风场和波浪场,并与卫星高度计资料、散射计风场、再分析资料以及实测浮标资料进行了比较,验证了模式的准确性。基于这套模式结果,系统地分析了江苏近海的风场和波浪场的多时间尺度变化:季节变化、日变化以及季节内变化(台风、寒潮)。分析结果表明:苏北近海海域的风速、有效波高和涌浪在冬季和秋季较大、春季和夏季较小;冬季盛行西北风,常浪向为西北向,夏季盛行东南风,常浪向为东南向。风场和波浪场还具有显著的日变化特征,且日变化存在季节变化规律,离岸越近海域日变化特征越明显。同时,江苏近海还会经历季节内尺度的强天气过程的影响,比如台风和寒潮。 相似文献
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准确预测波浪透射对于维护港内水域平稳、保障港内船舶稳定具有重要意义。基于567组透浪试验数据,采用基因表达式编程(gene expression programming,简称GEP)算法预测波浪透射。主要研究内容包括:确定GEP算法的最优输入变量组合;建立透浪系数与最优组合变量的定量关系;探究GEP算法的预测精度随训练组数变化的规律;并对输入变量进行了敏感性分析。研究结果表明,GEP算法的最优输入变量组合为深水波陡、相对堤宽和相对水深;训练组数较少时,GEP算法的预测精度不高,当训练组数提高至300组,预测的精度已经达到较高水平,且精度随着训练组数的继续增加提高不大; GEP算法的预测精度远远高于前人的经验公式;相较于相对堤宽和相对水深,深水波陡对波浪透射影响更为显著。本研究表明,GEP算法可作为一种新的方法研究波浪透射,为后续研究与应用提供参照。 相似文献
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台湾岛地处亚欧大陆和太平洋交界处,台风、东北季风等所引起的海洋灾害频繁,所以建立完备的海洋水文观测体系显得尤为重要。中国台湾自主建置完成的近海水文观测体系由资料浮标站、观测桩、潮位站、岸边气象站、雷达测波站等多种近海水文观测系统构建组成;同时,为确保观测体系的准确性和规范性,还建立了数据品质管理系统和标准化作业模式。在近海水文观测数据的分析方面,尝试应用新的数学分析方法,如通过EMD（empirical mode decomposition）方法探讨风暴潮水位变化,利用小波转换从雷达观测影像中分析近岸波浪信息,以及发展数据同化技术将观测数据应用于作业化波浪现报、预报模式。此外,近海水文观测体系在社会应用方面有着很大的发展潜质。 相似文献
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以2000年为例,采用SWAN波浪数值模型对浙江近海海域的波浪进行了全年模拟计算,并计算获得年、月平均波功率密度分布。研究表明,浙江近岸海域年平均波功率密度约为2~6 kW·m-1,往外海逐渐增大;同时季节变化明显,秋、冬季节波功率密度较大,春、夏季节较小。另外,通过对浙北、浙中和浙南3个近海海区的波浪出现频率和波功率密度随波高和周期变化的分析可知,浙北海域波功率密度比较高的波高及周期范围和波浪出现频率较高范围较为接近,而其对应平均波功率密度相对较低;浙南海域波功率密度比较高的范围所对应的平均波功率密度较高,而与波浪出现频率较高的范围则略有差异;浙中海域居两者之间。总体而言,浙江近海波浪能资源丰富,且全年中可开发与利用的波浪能出现频率较高。 相似文献
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《海洋技术学报》2023,(2)
本文基于唐山近海海域1#、2#浮标2017年4月至11 月实时海浪观测数据及部分风速风向数据, 对唐山近海海域波浪有效波高、有效波向、有效波周期等波参数特征进行了统计分析, 并利用origin 软件对波参数与风速、风向相关性进行了研究。研究结果表明： 1#、2# 浮标海域常浪向为SSW、SW、SSE, 常浪向有效波高均以0.2 ～ 0.4 m 小浪及3 ～ 4 s 短周期为主,有效波高1 m 以上较大波浪极少出现; 该海域波浪以风浪为主, 波浪破碎速度较快, 有效波高与风速相关性较强, 相关系数r 为0.71, 风向与波向、有效波高与周期基本无相关性, 该研究资料可为海上活动及防灾减灾提供技术依据。 相似文献
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The paper examines the variability of wave overtopping parameters predicted by numerical models based on non-linear shallow water equations, due to the boundary conditions obtained from wave energy density spectra. Free surface elevation time series at the boundary are generated using the principle of linear superposition of the spectral components. The components' phases are assumed to be random, making it possible to generate an infinite number of offshore boundary conditions from only one spectrum.A reference case was provided by carrying out overtopping tests on a simple concrete structure in a wave flume. Numerical tests using the measured free surface elevation at the toe of the structure were carried out. Three parameters were analysed throughout the paper: the overtopping discharge, the probability of overtopping and the maximum overtopping volume. These showed very good agreement between the numerical solver prediction and the overtopping measurements. Subsequently, the measured spectra at the toe were used to generate a population of reconstructed offshore boundary time series for each test, following a Monte Carlo approach. A sensitivity analysis determined that 500 tests were suitable to perform a statistical analysis on the predicted overtopping parameters. Results of these tests show that the variability in the predicted parameters is higher for the smaller number of overtopping waves in the modelled range and decreases significantly as overtopping becomes more frequent. The characteristics of the distributions of the predictions have been studied. The average value of the three parameters has been compared with the measurements. Although the accuracy is lower than that achieved by the model when the measured time series are used at the boundary, the prediction is still fairly accurate above all for the highest overtopping discharges. The distribution of the modelled probability of overtopping was found to follow a normal distribution, while the maximum value follows a GEV one. The overtopping discharge shows a more complex behaviour, values in the middle of the tested range follow a Weibull distribution, while a normal distribution describes the top end of the range better.Results indicate that when the probability of overtopping is smaller than 5%, a sensitivity analysis on the seeding of the offshore boundary conditions is recommended. 相似文献
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Operational activities in the ocean like planning for structural repairs or fishing expeditions require real time prediction of waves over typical time duration of say a few hours. Such predictions can be made by using a numerical model or a time series model employing continuously recorded waves. This paper presents another option to do so and it is based on a different time series approach in which the input is in the form of preceding wind speed and wind direction observations. This would be useful for those stations where the costly wave buoys are not deployed and instead only meteorological buoys measuring wind are moored. The technique employs alternative artificial intelligence approaches of an artificial neural network (ANN), genetic programming (GP) and model tree (MT) to carry out the time series modeling of wind to obtain waves. Wind observations at four offshore sites along the east coast of India were used. For calibration purpose the wave data was generated using a numerical model. The predicted waves obtained using the proposed time series models when compared with the numerically generated waves showed good resemblance in terms of the selected error criteria. Large differences across the chosen techniques of ANN, GP, MT were not noticed. Wave hindcasting at the same time step and the predictions over shorter lead times were better than the predictions over longer lead times. The proposed method is a cost effective and convenient option when a site-specific information is desired. 相似文献
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Design of an offshore wind turbine requires estimation of loads on its rotor, tower and supporting structure. These loads are obtained by time-domain simulations of the coupled aero-servo-hydro-elastic model of the wind turbine. Accuracy of predicted loads depends on assumptions made in the simulation models employed, both for the turbine and for the input wind and wave conditions. Currently, waves are simulated using a linear irregular wave theory that is not appropriate for nonlinear waves, which are even more pronounced in shallow water depths where wind farms are typically sited. The present study investigates the use of irregular nonlinear (second-order) waves for estimating loads on the support structure (monopile) of an offshore wind turbine. We present the theory for the irregular nonlinear model and incorporate it in the commonly used wind turbine simulation software, FAST, which had been developed by National Renewable Energy Laboratory (NREL), but which had the modeling capability only for irregular linear waves. We use an efficient algorithm for computation of nonlinear wave elevation and kinematics, so that a large number of time-domain simulations, which are required for prediction of long-term loads using statistical extrapolation, can easily be performed. To illustrate the influence of the alternative wave models, we compute loads at the base of the monopile of the NREL 5MW baseline wind turbine model using linear and nonlinear irregular wave models. We show that for a given environmental condition (i.e., the mean wind speed and the significant wave height), extreme loads are larger when computed using the nonlinear wave model. We finally compute long-term loads, which are required for a design load case according to the International Electrotechnical Commission guidelines, using the inverse first-order reliability method. We discuss a convergence criteria that may be used to predict accurate 20-year loads and discuss wind versus wave dominance in the load prediction. We show that 20-year long-term loads can be significantly higher when the nonlinear wave model is used. 相似文献
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Significant wave height estimates are necessary for many applications in coastal and offshore engineering and therefore various estimation models are proposed in the literature for this purpose. Unfortunately, most of these models provide simultaneous wave height estimations from wind speed measurements. However, in practical studies, the prediction of significant wave height is necessary from previous time interval measurements. This paper presents a dynamic significant wave height prediction procedure based on the perceptron Kalman filtering concepts. Past measurements of significant wave height and wind speed variables are used for training the adaptive model and it is then employed to predict the significant wave height amounts for future time intervals from the wind speed measurements only. The verification of the proposed model is achieved through the dynamic significant wave height and wind speed time series plots, observed versus predicted values scatter diagram and the classical linear significant wave height models. The application of the proposed model is presented for a station in USA. 相似文献
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海浪直接影响海上活动和航行安全,同时也蕴藏着巨大的可再生能源,对海浪核心参数之一波高预测至关重要。基于2015年7月～2022年6月山东小麦岛(36°N,120.6°E)站点实测的波高数据,利用反向传播神经网络(back-propagation neural network,BPNN)、长短记忆网络(long short-term memory, LSTM)和支持向量机回归(support vector regression, SVR)三种机器学习模型对波高进行预测,并分析了瑞利参数的引入对预测结果的影响。结果显示,模型输入项引入瑞利参数后,对1 h和6 h波高预测提升效果有限,预测值与测试集的相关性提升不超过0.02,均方根误差的降低不超过0.01 m;在12h和24h的预测中,BPNN和LSTM模型预测结果相关性提升0.03～0.07,均方根误差降低0.02～0.03m,而SVR模型预测结果变化不显著。说明瑞利参数有助改善BPNN和LSTM模型中长期海浪预报。此外,特征扰动方法(机器学习中特征重要性的计算方法之一)验证了瑞利参数在波高预测中的重要性,瑞利参数的引入为波高的机器学习预... 相似文献
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A.J.H.M. Reniers M.J. Groenewegen K.C. Ewans S. Masterton G.S. Stelling J. Meek 《Coastal Engineering》2010
The accuracy of nearshore infragravity wave height model predictions has been investigated using a combination of the spectral short wave evolution model SWAN and a linear 1D SurfBeat model (IDSB). Data recorded by a wave rider located approximately 3.5 km from the coast at 18 m water depth have been used to construct the short wave frequency-directional spectra that are subsequently translated to approximately 8 m water depth with the third generation short wave model SWAN. Next the SWAN-computed frequency-directional spectra are used as input for IDSB to compute the infragravity response in the 0.01 Hz–0.05 Hz frequency range, generated by the transformation of the grouped short waves through the surf zone including bound long waves, leaky waves and edge waves at this depth. Comparison of the computed and measured infragravity waves in 8 m water depth shows an average skill of approximately 80%. Using data from a directional buoy located approximately 70 km offshore as input for the SWAN model results in an average infragravity prediction skill of 47%. This difference in skill is in a large part related to the under prediction of the short wave directional spreading by SWAN. Accounting for the spreading mismatch increases the skill to 70%. Directional analyses of the infragravity waves shows that outgoing infragravity wave heights at 8 m depth are generally over predicted during storm conditions suggesting that dissipation mechanisms in addition to bottom friction such as non-linear energy transfer and long wave breaking may be important. Provided that the infragravity wave reflection at the beach is close to unity and tidal water level modulations are modest, a relatively small computational effort allows for the generation of long-term infragravity data sets at intermediate water depths. These data can subsequently be analyzed to establish infragravity wave height design criteria for engineering facilities exposed to the open ocean, such as nearshore tanker offloading terminals at coastal locations. 相似文献
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海上结构设计包括对荷载和响应的可靠性评估。对结构进行全面长期响应分析繁琐且费时,故将基于逆一阶可靠性方法的环境包络线进行海上结构概率可靠性分析,对结构的长期响应进行近似估计。在二维标准正态空间中画出与重现期相对应的圆,将圆离散为点后通过Rosenblatt变换转化为环境参数空间中的点来形成闭合的环境包络线。描述海洋环境条件的模型对绘制环境包络线极为重要,基于我国南海荔湾海域40年波浪模拟数据,建立了描述南海波浪的Weibull-Gev条件分布模型,进而绘制南海有效波高—谱峰周期包络线,并与张力腿平台(TLP)系泊张力的长期响应预报结果对比,给出南海海域在波浪作用下应用环境包络线法预报TLP系泊张力的分位数,为未来南海TLP设计中系泊张力预报提供快速估算方法。 相似文献
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Traditional wave steepness s=H/L does not define steep asymmetric waves in a random sea uniquey. Three additional parameters characterising single zero-downcross waves in a time series are crest front steepness, vertical asymmetry factor and horizontal asymmetry factor. Results for steepness and asymmetry from zero-downcross analysis of wave data obtained from full scale measurements in deep water on the Norwegian continental shelf in 58 time series are presented. The analysis demonstrates clearly the asymmetry of both “extreme waves” and the highest waves. The period and height of the highest waves are also given together with their correlation to spectral parameters. The measured maximum wave heights are also compared with predicted values of maximum wave heights showing good agreement. 相似文献
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The influences of the three types of reanalysis wind fields on the simulation of three typhoon waves occurred in 2015 in offshore China were numerically investigated. The typhoon wave model was based on the simulating waves nearshore model (SWAN), in which the wind fields for driving waves were derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-Interim (ERA-interim), the National Centers for Environmental Prediction climate forecast system version 2 (CFSv2) and cross-calibrated multi-platform (CCMP) datasets. Firstly, the typhoon waves generated during the occurrence of typhoons Chan-hom (1509), Linfa (1510) and Nangka (1511) in 2015 were simulated by using the wave model driven by ERA-interim, CFSv2 and CCMP datasets. The numerical results were validated using buoy data and satellite observation data, and the simulation results under the three types of wind fields were in good agreement with the observed data. The numerical results showed that the CCMP wind data was the best in simulating waves overall, and the wind speeds pertaining to ERA-Interim and CCMP were notably smaller than those observed near the typhoon centre. To correct the accuracy of the wind fields, the Holland theoretical wind model was used to revise and optimize the wind speed pertaining to the CCMP near the typhoon centre. The results indicated that the CCMP wind-driven SWAN model could appropriately simulate the typhoon waves generated by three typhoons in offshore China, and the use of the CCMP/Holland blended wind field could effectively improve the accuracy of typhoon wave simulations. 相似文献