A dipole mode at thermocline layer in the tropical Indian Ocean

Temperature data at different layers of the past 45 years were studied and we found adiploe mode in the thermocline layer (DMT): anomalously cold sea temperature off the coast of Sumatra and warm sea temperature in the western Indian Ocean. First, we analyzed the temperature and the temperature anomaly (TA) along the equatorial Indian Ocean in different layers. This shows that stronger cold and warm TA signals appeared at subsurface than at the surface in the tropical Indian O-cean. This result shows that there may be a strong dipole mode pattern in the subsurface tropical Indian Ocean. Secondly we used Empirical Orthogonal Functions (EOF) to analyze the TA at thermocline layer. The first EOF pattern was a dipole mode pattern. Finally we analyzed the correlations between DMT and surface tropical dipole mode (SDM), DMT and Nino 3 SSTA, etc. and these correlations are strong.     

A probability distribution for depth-limited extreme wave heights in a sea state

A model for the depth-limited distribution of the highest wave in a sea state is presented. The distribution for the extreme wave height is based on a probability density function (pdf) for depth-limited wave height distribution for individual waves [Méndez, F.J., Losada, I.J., Medina, R. 2004. Transformation model of wave height distribution. Coastal Eng, Vol. 50, 97:115.] and considers the correlation between consecutive waves. The model is validated using field data showing a good representation of the extreme wave heights in the surf zone. Some important statistical wave heights are parameterized obtaining useful expressions that can be used in further calculations.     

Optimization Mathematical Model of Pile Forces for Offshore Piled Breasting Dolphins

An optimization mathematical model of the pile forces for piled breasting dolphins in the open sea under various loading conditions is presented. The optimum layout with the well distributed pile forces and the least number of piles is achieved by the multiplier penalty function method. Several engineering cases have been calculated and compared with the result of the conventional design method. It is shown that the number of piles can be reduced at least by 10%—20% and the piles‘ bearing state is improved greatly.     

现场海域水平扩散系数的探讨 Ⅱ．黄河三角洲埕北海域的计算

根据Ｔａｙｌｏｒ的湍流扩散理论和Ｈａｙ、Ｐａｓｑｕｉｌｌ提出的拉格朗日流和欧拉流的相关函数的相似性，用黄河三角洲埕北海域的实测资料，按四种不同方案计算出该海域的水平扩散系数和谱密度分布。指出：该海区潮流扩散系数主要受潮流的影响，其分布特征与潮流的分布基本一致，所求的水平扩散系数主要是由周期性的潮运动给予潮流扰动所致。方案４是通过富氏变换滤波消去了周期性潮流扰动，本方案计算的水平扩散系数是由周期为６ｈ以下的小尺度涡提供能量。     

Observations and Estimations of Directional Spectrum of Sea Waves

The directional spectrum is one of the basic characteristics of sea waves. The observations of directional spectrum of sea waves were successfully conducted at platform Bohai 8 during 1991 and 1992 using a wave gage array for the first time in China. Based on the field data, the directional spectrum which depends on the wave growth is given in this paper. Before observations, the effects of the type of gage array, the distance between the gages and the platform itself on the measured results and the precision of some methods for estimating the directional spectrum were investigated and compared with the methods of numerical simulations and model tests of multi-direcitonal irregular waves. This ensures the quality of the observations and estimations of the directional spectrum.     

Hydroelastic Analysis of Very Large Floating Structures Using Plate Green Functions

1 .IntroductionRecentlygreatinteresthasbeenshowninthedevelopmentofverylargefloatingstructuressuchasMegaFloatofJapan (Isobe ,1 999)andMOBofUSA (Remmers ,1 999) .Owingtotheirextremelargesizeandgreatflexibility ,thecouplingbetweenthestructuraldeformationandfluidmotionissignifi cant.Thisisatypicalproblemofhydroelasticity .Efficientandaccurateestimationofthehydroelasticresponseofverylargefloatingstructuresinwavesisveryimportantfordesign .Manymethodshavebeenproposedinliteratureforthepredictiono…     

河口潮位在频域内的一种插补模型

若把河口潮位时间序列简单地看为单输入和输出线性系统模型的输入输出信号，借助频谱分析可以将它们在频域内的关系建立起来，用来进行潮位序列的插补，带通滤波技术的应用可使模型的计算精度大大提高     

Expanded adaptive fuzzy sliding mode controller using expert knowledge and fuzzy basis function expansion for UFV depth control

Generally, the underwater flight vehicle (UFV) depth control system operates with the following problems: it is a multi-input multi-output (MIMO) system, it requires robustness, a continuous control input, and further, it has the speed dependency of controller parameters. To solve these problems, an expanded adaptive fuzzy sliding mode controller (EAFSMC), which is based on the decomposition method designed by using an expert knowledge and the decoupled sub-controllers and composition method designed by using the fuzzy basis function expansions (FBFEs), is proposed. To verify the performance of the EAFSMC, the depth control of UFV in various operating conditions is performed. Simulation results show that the EAFSMC solves all problems experienced in the UFV depth control system online.     

The Huelva (Spain) Tsunami-Ready Station and Its Interaction with Storm Emma (March 2018)

Abstract

The sea level station operating since 1996 at Mazagón (Huelva, Spain) has been progressively upgraded to fit tsunami warning requirements, due to its location in one of the main regions at risk. Its radar water level sensor was complemented in 2017, with the addition of a pressure sensor. The performance of both sea level sensors and their response to sea level oscillations, at different frequencies, is assessed. Particular emphasis is put on the effect of extreme events, such as Storm Emma, when alternative methods to obtain 1-min data are tested, in contrast to the one based on arithmetic means. The overall differences are small, for the whole period of study (centered-root-mean-square-error below 1?cm, for 5-min, and hourly data; similar tidal parameters and sea level oscillations with periods between 30?s and 5?min). However, during Storm Emma, the pressure sensor presents sensibly lower readings than the radar, with the centered-root-mean-square-error rising to 80?mm on the March 2^nd 2018. A new method to compute 1-min data, based on medians, reduced this value to 10?mm for the same day.