风浪波群中波高分布研究

在实验室风浪槽中观测风浪,发现波群连长是影响波群中波高分布的重要因素,随着波群连长增大,波群中波高分布信息熵增大。当以平均波高无因次化,连长较大时波群中波高累积概率明显大于连长较小时情形。波群中波高分布受谱宽度影响。当谱宽度增大,波群中波高累积概率降低。谱宽度和波群连长对波群中波高累积概率的影响相当。引进体现波群特性的1个无因次化波高参量研究波群中波高累积概率。     

风浪波高间相关性和在波群中波高累积概率

通过分析实验室风浪资料,研究风浪波高间的相关性以及波群中波高累积概率问题,发现风浪波高间相关性虽然主要发生在相邻波之间,但在隔1个波和隔2个波的波高间仍存在一定的相关性。谱宽度对波高间的相关性产生影响,但在相邻波、隔1个波和隔2个波情形下,谱宽度对波高间的相关性的影响方式不同。在相邻波情形下,谱宽度主要影响较大波高间的相关性,对各种高度波高间的总体相关性影响很小。而在隔1个波和隔2个波情形下,谱宽度对各种高度波高间的总体相关性有明显影响。根据实验结果提出含有波高相关因子的波群中多个波波高累积概率分布。     

非线性海浪波面与波高的统计分布

采用风浪谱参量化的方法将随机波面无因次化,把波面与波高概率分布的各阶矩展开为谱宽度根方的幂级数,并由此导出波面与波高的统计分布。结果表明,在准确至零阶和一阶时,风浪分别退化为静止海面和单色波;在准确至二阶时,波面为线性模型,即波面服从正态分布;而在准确至三阶以上时,波面分布与Longuet-Higgins导出的非线性海浪模型的Gram-Charlier形分布具有同效益;并在准确至三阶时,导出一种新的波高分布,此分布函数以Longuet-Higgins等给出的Rayleigh分布作为二阶近似的特例。     

非线性效应对风浪波面极大值和极小值分布的影响

通过分析实验室风浪观测结果研究非线性效应对波面极大值和极小值分布的影响。波面极大值和极小值累积概率的差异表明 ,与线性理论相比 ,波面极小值在平均波面以下的位置偏高。对实验结果的进一步分析表明 ,非线性效应使波面极大值在平均波面以上总概率高于线性理论结果 ,而概率密度峰值处波面极大值高度略低于线性理论结果。波面极小值在平均波面以上各位置出现的概率均高于线性理论结果 ,在平均波面以下的较低位置 ,波面极小值出现概率明显低于线性理论结果。     

粗糙度与风浪特征量关系的研究

在实验室风浪槽中观测风浪和风速,研究粗糙度与波面特征量的关系,发现风浪谱宽度增加,粗糙度增大。在窄谱时,粗糙度随谱宽的增加变化不明显,当波陡降低,粗糙度降低;在宽谱时,当谱宽度增加,即使波陡降低,粗糙度仍可增大。这一结果表明,波陡不足以完全决定粗糙度。当风浪波龄增加,粗糙度呈下降趋势,但由于谱宽度对粗糙度的影响,当波龄增加,部分波浪可有较大的粗糙度。由于这一因素,在粗糙度与波龄关系的观测结果中,数据点的散落不完全由观测误差造成。     

风浪波高和周期的联合概率密度分布

本文采用有代表性的44008美国国家浮标站2003年1～3月实测的海浪谱密度资料,选取三次大风过程进行风浪谱分析。通过对实测平均海浪谱与PM谱、JONSWAP谱及Torsethaugen谱的比较,得到PM谱拟和最好。然后用国际上最先进的随机波分析方法,根据协方差矩阵的循环嵌套技术,以实测平均谱与PM谱为靶谱,对随机波面进行模拟。得到由模拟波面统计的特征值及估计的谱与实测谱结果极为相近,谱峰及谱峰频率都基本一致。说明利用模拟波面研究海浪具有代表性,它可以反映实测海浪的特征。利用Longuet-Higgins(1983)模型计算波高-周期联合概率密度分布,得到变换高斯过程计算的波高、周期联合分布与实测情况基本相同,更好地描述了波高-周期联合概率密度分布。     

北礵岛附近海域夏季海浪波高-周期分布特征

利用2016年夏季(6—8月)北礵岛附近海域的实测波浪数据,统计分析该海域海浪的波高特征值,探讨各特征波高与平均波高及有效波高之间的关系,找出较适用于该海域的波高分布、周期分布以及波高和周期的联合分布。结果表明:该海域有效波高的平均值为0.73 m,最大值为2.96 m,平均周期的平均值为4.50 s;各特征波高与平均波高及有效波高的比值普遍小于Rayleigh分布理论值;采用双参数Weibull分布,利用最小二乘法拟合出的波高分布和周期分布较适用于该海域。根据实测波高和周期联合分布结果,与已有的波高和周期理论分布进行对比,发现Longuet-Higgins改进分布和孙孚分布较适用于该海域的波高和周期联合分布特征。     

西太平洋赤道海域秋季混合浪特征及其谱拟合

根据西太平洋赤道海域秋季实测海浪资料,分析了该海域的混合浪特征,拟合出混合浪的波高、周期分布函数及波高-周期联合分布函数。应用文圣常等提出的深水风浪谱公式,对其稍作改变后拟合涌浪谱;应用他们的改进理论风浪谱公式拟合风浪谱,两分谱公式叠加为混合海浪谱公式。对混合海浪谱的拟合表明,拟合效果良好。     

风浪统计性质的实验研究

本文为风浪统计性质的实验研究的第2部分.利用在第1部分中获取的风浪资料,着重讨论波高与周期的联合统计分布及其随风速、风区、水深、坡度等的变化规律.此外,还系统分析了理论结果与实际间存在差异的原因及影响统计分布的有关参数.     

风浪统计性质的实验研究──Ⅱ．波高与周期的联合统计分布

本文为风浪统计性质的实验研究的第２部分。利用在第１部分中获取的风浪资料，着重讨论波高与周期的联合统计分布及其随风速、风区、水深、坡度等的变化规律。此外，还系统分析了理论结果与实际间存在差异的原因及影响统计分布的有关参数。     

广东阳西近岸海域波浪的分布特征

通过对广东阳西近岸测站1a实测波浪资料及岸边同期风资料的整理与分析,探讨了该海域的波浪特性,得出研究海域不分方向H1/10年平均值为1.00 m,常浪向为SE向,出现的频率为38.35%,强浪向为SE向,观测期间的最大波高出现在0814号"黑格比"台风期间,Hmax值为8.31 m.用已有的理论分布函数对实测统计数据进行拟合,筛选出研究海域的波高分布、周期分布及波高与周期联合分布的特征,结果表明双参数威布尔理论波高分布、杨正己威布尔周期分布、朗格-赫金斯83模式或者孙孚模式较为适用于本海区的波高分布、周期分布、波高周期联合分布;结合相应的风速风向资料,运用回归分析方法,建立了该地区的波高与风速之间、波高与波周期之间的关系.     

欧洲北海海域波高区间分布概率研究

为了研究欧洲北海海域的波高全区域概率分布情况,从而为海洋平台等海洋浮式结构物的选址和结构设计提供依据。首先基于Global Waves Statistics(GWS)提供的实测数据,确定典型计算工况的发生概率;同时考虑实测数据中极端波浪环境下的数据缺失导致大波高分布概率偏小的问题,利用三参数Weibull分布确定不同重现期下的极值风速,作为典型计算工况的补充。以不同风速、风向的定常风场为输入项,利用第三代海浪数值模型SWAN模型,对北海全区域波高进行数值模拟。将数值模拟的稳态形式依照各工况的发生概率进行归一化累加处理,认为其结果可以表征全区域的波高概率分布情况。以波高概率分布的计算结果为依据,分析北海海域波浪环境的统计学特征,发现有效波高为7 m以上的大波高频发区在北海北部区域有大范围分布;有效波高4～5 m为北海东北区域的多发海况,极端海况下的有效波高主要分布于7～14 m区间,在地形突变区域的波高发生显著变化。     

Dependence of Wave Height Distribution on Spectral Width and Wave Steepness

In this paper experimental wind wave data are analyzed. It is found that differences in spectral width will give rise to differences in wave height distribution. The effect of spectral width on the distribution is mainly in the high wave range. The effect of wave steepness is in low, medium and high wave ranges. In the high wave range the effect of spectral width is comparable to that of wave steepness. Differences in spectral width in the observations may give rise to discrepancies in the result when wave steepness is the only parameter in the distribution.     

Wave Energy Estimation by Using A Statistical Analysis and Wave Buoy Data near the Southern Caspian Sea

Statistical analysis was done on simultaneous wave and wind using data recorded by discus-shape wave buoy. The area is located in the southern Caspian Sea near the Anzali Port. Recorded wave data were obtained through directional spectrum wave analysis. Recorded wind direction and wind speed were obtained through the related time series as well. For 12-month measurements(May 25 2007-2008), statistical calculations were done to specify the value of nonlinear auto-correlation of wave and wind using the probability distribution function of wave characteristics and statistical analysis in various time periods. The paper also presents and analyzes the amount of wave energy for the area mentioned on the basis of available database. Analyses showed a suitable comparison between the amounts of wave energy in different seasons. As a result, the best period for the largest amount of wave energy was known. Results showed that in the research period, the mean wave and wind auto correlation were about three hours. Among the probability distribution functions, i.e Weibull, Normal, Lognormal and Rayleigh, "Weibull" had the best consistency with experimental distribution function shown in different diagrams for each season. Results also showed that the mean wave energy in the research period was about 49.88 k W/m and the maximum density of wave energy was found in February and March, 2010.     

响水近岸海域波浪特性研究

基于响水波浪站累计一整年的现场观测资料，分析了波高和波周期的年内变化特性，研究了波浪的统计特性和波谱特性，并总结归纳了该海域各特征波要素之间以及各波谱参数之间的转换关系。结果显示:响水海域全年有效波高的变化幅度在0.10~2.80 m之间，年平均值为0.56 m；最大波高的变化幅度在0.15~5.58 m之间，年平均值为0.93 m；平均波周期的变化范围为1.91~9.02 s，年平均值为3.90 s。夏季大波高发生频率明显要小于冬、春季节，波浪季节性变化较为显著。就波高和波周期分布而言，通过拟合得出的Weibull分布较为适合本海域实测波高分布和波周期分布。波谱特性方面，本海域双峰谱占到总数的62.5%，且低频谱峰值普遍高于高频谱峰值，其中低频谱峰出现在0.04 Hz左右，高频谱峰则出现在0.15~0.20 Hz之间，分别为本海域涌浪和风浪所集中的频率区间。采用回归分析方法进一步分析了各特征波要素之间以及各波谱参数之间的关系，发现多数波参数之间存在显著的相关性，但受波浪浅水变形影响，各参数之间的比值与理论深水关系有所区别。本文的研究成果可为沿海建筑物的设计以及防灾减灾提供参考和依据。     

Statistical characteristics of long waves nearshore

The random long wave runup on a beach of constant slope is studied in the framework of the rigorous solutions of the nonlinear shallow water theory. These solutions are used for calculation of the statistical characteristics of the vertical displacement of the moving shoreline and its horizontal velocity. It is shown that probability characteristics of the runup heights and extreme values of the shoreline velocity coincide in the linear and nonlinear theory. If the incident wave is represented by a narrow-band Gaussian process, the runup height is described by a Rayleigh distribution. The significant runup height can also be found within the linear theory of long wave shoaling and runup. Wave nonlinearity nearshore does not affect the Gaussian probability distribution of the velocity of the moving shoreline. However the vertical displacement of the moving shoreline becomes non-Gaussian due to the wave nonlinearity. Its statistical moments are calculated analytically. It is shown that the mean water level increases (setup), the skewness is always positive and kurtosis is positive for weak amplitude waves and negative for strongly nonlinear waves. The probability of the wave breaking is also calculated and conditions of validity of the analytical theory are discussed. The spectral and statistical characteristics of the moving shoreline are studied in detail. It is shown that the probability of coastal floods grows with an increase in the nonlinearity. Randomness of the wave field nearshore leads to an increase in the wave spectrum width.     

Application of MEP Method to the Study of Statistical Properties of Random Waves

—The maximum entropy principle(MEP)method and the corresponding probability evaluationmethod are introduced,and the maximum entropy probability distribution expression is deduced in mo-ment of the second order.Fully developed wave height distribution in deep water and wave height and peri-od distribution for different depths in wind wave channel experiment are obtained from the MEP method,and the results are compared with the distribution and the experimental histogram.The waveheight and period distribution for the Lianyungang port is also obtained by the MEP method,and the re-sults are compared with the Weibull distribution and the field histogram.