粤东近岸深水区周年波浪特征分析

  目的  根据粤东近岸深水区1a的现场实测海浪资料,主要对该海域周年波浪基本特征进行统计分析。  方法  首先对波高和周期特征值进行逐月统计,得到全年基本分布特征;再对波向进行统计,得到波向季节特征;再对波高-周期联合分布和波高与周期之间的关系进行探讨;最后对典型台风浪的特征进行研究。  结果  结果表明:（1）全年H_s平均值为1.52 m,H_max为15.97 m,全年12月、1月和2月的H_s平均值最大,H_max由台风“山竹”造成;（2）受季风季候和热带气旋影响,全年常浪向和强浪向分别为ENE向和SE向;（3）全年波浪类型主要以风浪成分为主,对波高与周期的相关关系进行拟合;（4）根据“山竹”台风浪实测数据,波高和周期都有显著的升高和降低过程。通过海浪谱分析,台风期间经历了从双峰谱向单峰谱的演变,说明台风期间的波浪类型主要为风涌混合浪,谱峰值于9月16日6时达到最大值96.74 m2/Hz,谱峰频率为0.07 Hz。  结论  研究成果可以为相关海洋工程的设计提供技术参考。     

基于Copula函数的邕宁水利枢纽多时段施工导流风险及方案决策

为了研究不过水围堰多时段施工导流风险问题,提出了基于Monte-Carlo方法和Copula函数的施工导流水文风险计算模型。考虑各导流时段施工洪峰流量之间的相关性,根据实测水文资料选取Copula函数拟合,建立联合分布,采用随机模拟技术生成导流时段洪峰流量并统计风险,进而计算了邕宁水利枢纽二期导流风险,并利用TOPSIS决策模型进行了方案决策。结果表明,联合分布拟合效果良好,能更加合理地分析风险率,且延长至前汛期的围堰挡水方案为该工程的较优方案,带来了巨大的经济效益。     

多变量水文联合分布方法及Copula函数的应用研究

简介了水文事件中的多变量联合分布计算方法,系统总结了Copula函数的原理、性质、水文计算中常用的函数类型、参数估计方法及拟合检验方法,探讨了Copula函数在水文方面的应用前景.     

随机波作用下圆柱形垂荡浮子水动力行为的数值研究

建立随机波作用下垂荡浮子三维水动力数学模型,并与随机波理论频谱和随机波作用下垂荡浮子试验数据进行有效验证。利用验证后的模型对不同波况下,不同高度的圆柱形浮子垂荡行为进行计算分析,发现:1)浮子密度500 kg/m3时,浮子上行的最大速度略小于下行的最大速度,浮子上行的时间略大于下行的时间。2)随有效波高增加,浮子有效位移增加;随着谱峰周期增加,浮子有效位移基本呈现增加的趋势。有效波高较小时,谱峰周期对浮子有效位移的影响不大;有效波高较大时,谱峰周期对浮子有效位移的影响较大。3)浮子密度保持不变时,浮子高度对其有效位移的影响不大。     

基于Copula函数的柘林水库设计洪水频率分析

针对传统设计洪水频率分析采用单变量方法且不考虑变量间相关关系的问题,以江西省柘林水库坝址洪水为研究对象,采用Frank Copula函数构建洪峰与5d洪量的二元联合分布,并引入联合重现期的概念。结果表明,柘林水库坝址洪水主要受洪峰和洪量控制,峰量间存在良好的相关性;两变量方法推求的峰量联合设计值均大于单变量方法,各特征量的重现期均高于设计标准。可见Copula函数拟合度较高,计算所得频率设计值更符合洪水事件的内在规律以及工程实际要求,且同时可得不同情况下的峰量设计值组合,在水文领域具有广阔的应用前景。     

秦淮河流域不同频率降雨联合概率分析

秦淮河流域汛期雨量丰沛,洪水的特性受一日降雨量和多日降雨量影响,单考虑某一时段的降雨量不能全面反映流域洪灾的风险。选取P-Ⅲ型分布分别作为最大1日面雨量的边际分布,两参数对数正态分布作为最大3日面雨量、最大7日面雨量边际分布。在此基础上利用Gumbel Copula函数建立秦淮河流域最大1日面雨量、最大3日面雨量联合分布模型,利用Clayton Copula函数建立最大1日面雨量、最大7日面雨量联合分布模型,并计算了二维联合分布下的暴雨设计值和重现期。结果表明,两变量联合重现期小于同现重现期,基于二维Copula函数联合分布计算的暴雨设计值大于单变量分布计算的暴雨设计值,为秦淮河流域的防洪防涝提供了参考。     

基于Copula函数的西南岩溶流域多变量洪水频率分析

基于西南岩溶区澄碧河流域平塘水文站年最大场次洪水数据,利用Copula函数建立多维洪水变量的联合分布并计算联合、同现重现期。结果表明,Frank Copula对洪峰—洪量二维联合分布的拟合效果最优(R_(RMSE)=0.041 1,A_(AIC)=-56.2),Gumbel Copula对洪峰—历时二维联合分布的拟合效果最优(R_(RMSE)=0.0482,A_(AIC)=-53.3),Gaussian Copula对洪量—历时二维联合分布的拟合效果最优(R_(RMSE)=0.046 0,A_(AIC)=-54.2),Gumbel Copula对洪峰—洪量—历时的三维联合分布拟合效果最优(R_(RMSE)=0.049 2,A_(AIC)=-53.0);洪水单变量重现期大于多变量联合重现期(如T=100 a,相应的T_(aqw)=52.3 a、T_(aqt)=79.9 a、T_(awt)=60.6 a和T_(aqwt)=35.7 a),小于多变量同现重现期(如T=100a,相应的T_(oqw)=980.2 a、T_(oqt)=130.1 a、T_(owt)=267.4 a和T_(oqwt)=260.3 a)。研究结果可为岩溶区流域工程防洪安全评价提供新的选择。     

基于Copula函数的长江堤防岸线土体参数分布模型研究

针对二维独立分布不能考虑变量间相关性，导致堤防边坡稳定性的可靠度计算结果不够准确的问题，基于171组长江堤防岸线土体抗剪强度试验数据，采用Copula函数研究长江堤防岸线土体抗剪强度参数间相关性，利用AIC、BIC准则识别最优边缘分布与Copula函数，构建二维联合分布模型，并分析数据量对参数间相关结构识别的影响。结果表明，基于Copula函数的二维联合分布模型能够较准确地表征长江堤防岸线土体参数间的相关性；当数据量大于24组时，AIC、BIC准则可准确识别最优Copula函数，为堤防边坡可靠度计算和Copula函数模型的构建提供参考。     

基于混合Copula优化算法的风速预测方法研究

针对风电场中各风电机组风速之间存在的复杂时空相关性问题,提出一种基于混合Copula优化算法的风电场风速预测方法。该方法首先分析单一Copula函数拟合优度检验,选取合适Copula函数进行组合;其次,构建混合Copula函数模型对风电场内多风电机组风速相关性进行分析;最后应用最大期望（EM）算法求解模型相关系数并完成风速预测。结合优化算法,改进Copula函数能很好地解决风速相关性问题,为获取准确风速预测值奠定基础。以中国某地区风电场风电机组实测风速数据为例对所提方法进行验证,实验结果表明该模型可在准确分析风速相关性的基础上提高风速预测准确性。     

基于综合Copula函数的风电功率相关性分析及其在无功优化中的应用

相同区域内的风电场风电功率之间存在较强的相关性,基于相关性分析理论,对5种Copula函数特性进行逐一分析,分别对某地区存在相关性的实际风电功率进行拟合和对比,进而构建综合Copula函数模型,对模型参数采用EM方法进行估计,并对构建的综合Copula函数进行拟合优度检验和对比,选取最优函数组合,运用多场景技术构建的两风电出力场景,对实际系统进行无功优化,验证了综合Copula函数模型在无功优化中运用的合理性和有效性。     

Trivariate maximum entropy distribution of significant wave height,wind speed and relative direction

A trivariate maximum entropy distribution of significant wave height, wind speed and the relative direction is proposed here. In this joint distribution, all the marginal variables follow modified maximum entropy distributions, and they are combined by a correlation coefficient matrix based on the Nataf transformation. The methods of single extreme factors and of conditional probability are presented for the joint design of trivariate random variables. The corresponding sampling data about significant wave heights, wind speeds and the relative directions from a location in the North Atlantic is applied for statistical analysis, and the results show that the trivariate maximum entropy distribution is sufficiently good to fit the data, and method of conditional probability can reduce the design values efficiently.     

Joint probability design of marine environmental elements for wind turbines

Decommission platforms can be used as the foundation of offshore wind turbines. In order to reduce the costs of wind power, the joint probability method is applied in the joint design of marine environmental elements. Based on copulas and univariate maximum entropy margins, multivariate maximum entropy distributions are constructed. Sample data of annual maximum significant wave height and corresponding wind speed and current velocity at Point 2 in Lianyungang Harbour of China is applied to testify the efficiency of trivariate maximum entropy distributions. The marginal fittings of univariate maximum entropy distributions and the trivariate data fitting based on normal copula fit the data well. The method of conditional probability can present a joint design of significant wave height and corresponding wind speed and current velocity.     

Environmental contours for circular‐linear variables based on the direct sampling method

Environmental contours are often used in the design of engineering structures to identify extreme environmental conditions that may give rise to extreme loads and responses. The perhaps most common application of environmental contours is for wave climate variables such as significant wave height and wave period. However, for the design of wind energy installations, the joint distribution of wind speed and wind direction may be equally important. In this case, joint modelling of linear (wind speed) and circular (wind direction) variables are needed, and methods for establishing environmental contours for circular‐linear variables will be required. In this paper, different ways of establishing environmental contours for circular‐linear variables will be presented and applied to a joint distribution model for wind speed and wind direction. In particular, the direct sampling approach to environmental contours will be modified to the case where one of the variables is cyclic. In addition, contours based on exceedance planes in polar coordinates will be established, and circular‐linear contours will also be calculated based on the inverse FORM (I‐FORM) approach.     

中小流域洪峰流量与水位联合分布的设计洪水分析

针对库岸堤坝防洪设计中洪峰流量与相应洪峰水位的联合分布研究的不足,采用Archimedean Gumbel-Hougaard Copula函数和Kendall分布函数分析洪峰流量和洪峰水位联合分布的重现期水平。以罗坝水流域结龙湾水文站1958～2013年的洪峰流量和相应洪峰水位为例,计算了二者联合分布下的"或"重现期、"且"重现期和Kendall重现期及其最可能的设计值。结果表明,洪峰流量和洪峰水位的遭遇条件概率显示存在多种防洪设计标准;对比"或"联合重现期和"且"重现期,Kendall重现期更准确地反映了洪峰流量和洪峰水位组合的风险率;以出现最大概率原理推算的不同洪峰流量和水位遭遇概率组合的Kendall重现期设计值为多种防洪标准选择与风险管理提供了更多的参考依据。     

基于ERA-Interim再分析数据的南海波浪能资源评估

利用欧洲中期天气预报中心近37 a（1979年1月—2015年12月）ERA-interim高分辨率（0.125°×0.125°）波浪再分析数据,计算南海海域的波浪能流密度、有效波高、平均周期、有效波时等波浪能参数,分析南海海域的波浪能资源时空分布特征。研究表明：1）南海波浪能资源呈现明显的季节分布特征,冬季资源最丰富,秋季次之,夏季最贫乏;2）波浪能资源丰富区位于吕宋海峡—中南半岛东南海域一线,呈东北—西南走向,大值区为吕宋海峡附近海域,波浪能流密度高达16 kW/m;3）综合考虑能流密度、有效波时间、与大陆最近港口距离和岛礁面积,建议A（112.33°E,16.81°N）岛屿作为开发利用的首选。     

Influence of the surface microstructure of the fuel cell gas diffusion layer on the removal of liquid water

The effective removal of water on the gas diffusion layer (GDL) surface and low flow channel resistance are essential for the water management of proton exchange membrane fuel cells (PEMFCs). In this paper, a 3D two-phase volume of fluid (VOF) model is used to compare and analyze the influence of different GDL surface microstructures on the liquid hydrodynamic behavior and optimize the design of the sine wave microstructure. The results show that the surface microstructure of the GDL has a more significant impact on the water removal and flow resistance coefficient in the flow channel, and the sine wave microstructure has substantial advantages. The sine wave peak and period significantly influence the water removal and flow resistance coefficient. As the peak increases, the average relative change rate and the flow resistance coefficient also increase; the influence of the period is opposite to the peak, and the continuous decrease of the period will accelerate the water removal in the flow channel. The sine wave's height and width have little impact on water removal and the flow resistance coefficient. When the sine wave A = 75 μm, T = 1.5, H = 15 μm, and L = 25 μm, good flow channel water removal and low resistance are achieved. This work has particular guiding significance for removing liquid water on the GDL surface and obtaining low flow channel resistance.     

波浪荷载下桩基-重力式复合结构的动力响应

桩基-重力式复合结构是一种能充分发挥高桩结构和重力式结构优点的新型开敞式深水码头结构型式,为分析波浪荷载作用下该结构的动力响应,利用ABAQUS建立模型,分析了沉箱高度为17、19、21m的桩基-重力式靠船墩的模态特性和波浪荷载下复合结构的上部墩台和中部桩柱的动力响应。结果表明,上部墩台和中部桩柱的位移响应随沉箱高度的增加而减小,墩台加速度响应则呈相反趋势;沉箱高度为17、19m时最大弯矩峰值发生在桩与沉箱的相交位置附近,沉箱高度为21m时最大弯矩峰值出现在桩与墩台的相交位置,不同沉箱高度时最大主应力峰值均发生在桩与沉箱的相交位置。研究结果可为桩基-重力式复合结构的应用提供参考。     

Numerical modeling of the effects of wave energy converter characteristics on nearshore wave conditions

Modeled nearshore wave propagation was investigated downstream of simulated wave energy converters (WECs) to evaluate overall near- and far-field effects of WEC arrays. Model sensitivity to WEC characteristics and WEC array deployment scenarios was evaluated using a modified version of an industry standard wave model, Simulating WAves Nearshore (SWAN), which allows the incorporation of device-specific WEC characteristics to specify obstacle transmission. The sensitivity study illustrated that WEC device type and subsequently its size directly resulted in wave height variations in the lee of the WEC array. Wave heights decreased up to 30% between modeled scenarios with and without WECs for large arrays (100 devices) of relatively sizable devices (26 m in diameter) with peak power generation near to the modeled incident wave height. Other WEC types resulted in less than 15% differences in modeled wave height with and without WECs, with lesser influence for WECs less than 10 m in diameter. Wave directions and periods were largely insensitive to changes in parameters. However, additional model parameterization and analysis are required to fully explore the model sensitivity of peak wave period and mean wave direction to the varying of the parameters.