On the two-layer high-level Green-Naghdi model in a general form

The traditional high-level Green-Naghdi(HLGN)model,which uses the polynomial as the shape function to approximate the variation of the horizontal-and vertical-velocity components along the vertical direction for each-fluid layer,can accurately describe the large-amplitude internal waves in a two-layer system for the shallow configuration(h_(2)/λ■1,h_(1)/λ■1).However,for the cases of the deep configuration(h_(2)/λ■1,h_(1)/λ=O(1)),higher-order polynomial is needed to approximate the variation of the velocity components along the vertical direction for the lower-fluid layer.This,however,introduces additional unknowns,leading to a significant increase in computational time.This paper,for the first time,derives a general form of the HLGN model for a two-layer fluid system,where the general form of the shape function is used during the derivation.After obtaining the general form of the two-layer HLGN equations,corresponding solutions can be obtained by determining the reasonable shape function.Large-amplitude internal solitary waves in a deep configuration are studied by use of two different HLGN models.Comparison of the two HLGN models shows that the polynomial as the shape function for the upper-fluid layer and the production of exponential and polynomial as the shape function for the lower-fluid layer is a good choice.By comparing with Euler’s solutions and the laboratory measurements,the accuracy of the two-layer HLGN model is verified.

用于非线性非平稳船舶运动极短期预报的一种复合自回归经验模态分解支持向量机回归模型（英文）

目的:基于支持向量机回归(SVR)模型在非线时间序列的预测能力及经验模态分解(EMD)方法在处理非线性非平稳性的优势,提出一种复合自回归经验模态分解支持向量机回归(AR-EMDSVR)模型,提高非线性非平稳船舶运动极短期预报精度。创新点:1.研究非线性非平稳船舶运动的极短期预报问题,提出一种复合的预报方法;2.基于不同层次的预报模型和模型试验数据,分析非线性非平稳性对极短期预报精度的影响。方法:1.在SVR模型中引入基于自回归(AR)预报端点延拓的EMD方法,形成复合的AR-EMDSVR预报模型;2.基于集装箱船模水池试验运动数据将AR-EMD-SVR模型与AR、SVR和EMD-AR三种模型进行比较,分析非线性非平稳性对极短期预报的影响以及不同模型的预报性能。结论:1.AR-EMD方法能够有效的克服非平稳对极短期预报模型(AR和SVR)在精度上所带来的不良影响;2.基于船模试验数据的预报结果表明:相较于AR、SVR和EMD-AR三种预报模型,基于AR-EMD-SVR模型的非线性非平稳船舶运动极短期预报结果具有更高的精度。

一种用于非线性非平稳波浪极短期预报的复合经验模态分解自回归模型（英文）

目的:相对于由能量平衡方程得到的数值预报模型和以神经网络为代表的非线性模型而言,自回归(AR)模型在波浪预报中具有计算效率高、自适应性强和建模所需的样本小等优点,但同时存在局限于平稳线性假设的缺陷。针对非线性非平稳波浪的极短期预报问题,提出一种复合的经验模态分解自回归预报模型,提高波浪预报精度。创新点:1.研究非线性非平稳波浪极短期预报问题,提出一种复合的预报方法;2.基于三个不同地理位置的海洋波浪实测数据对预测模型进行验证,并分析非线性非平稳性对波浪预报结果的影响。方法:1.在AR模型中引入经验模态分解(EMD)方法,形成复合的EMD-AR预报模型;2.分析实测波浪数据的非线性和非平稳性特点,并基于实测波浪数据获得AR模型和EMD-AR模型的预报结果;3.基于多种预报误差度量分析AR模型和EMD-AR模型的预报性能以及非线性非平稳性对波浪预报结果的影响。结论:1.波浪非线性和非平稳性会导致AR预报模型精度降低。预报误差中,幅值上的偏差主要由波浪的非线性引起,而相位上的偏差则是源于波浪的非平稳性;2.EMD方法能够有效地克服波浪非线性和非平稳性对AR模型在精度上所带来的不良影响,在精度上EMD-AR模型的预报结果较AR模型有较大提高。

Experiments and calculations of wave breaking and evolution of wave groups with high steepness

The evolution of the nonlinear wave groups in deep water is investigated through laboratory measurements and numerical analysis.Laboratory experiments are conducted in deep-water wave tank,focusing on the characteristics of breaking waves arising from the evolved wave train.Some quantitative results are obtained for the significant breaking wave train,including the surface elevation time series,the local geometry,and the energy dissipation.A nonlinear model for the evolution of the wave groups in deep water is developed by adding eddy viscosity dissipation terms in the High Level Irrotational Green-Naghdi(HLIGN)equations.The results of the simulation are compared with the laboratory measurements,and good agreement is observed for the evolved wave train.

On solitary wave in nonuniform shear currents

In this paper,steady solutions of solitary waves in the presence of nonuniform shear currents are obtained by use of the high-level Green-Naghdi(HLGN)model.We focus on large-amplitude solitary waves in strong opposing shear currents.The linear-type currents,quadratic-type currents and cubic-type currents are considered.In particular,the wave speed,wave profile,velocity field,particle trajectories and vorticity distribution are studied.It is demonstrated that presence of the nonuniform shear current modifies the velocity field and vorticity field of the solitary wave.

一种用于船舶纵-横联合减摇的预测控制器（英文）

目的:为提高船舶运动联合减摇效果,提出一种基于船舶运动及船舶水动力预报的联合减摇控制方法,并基于弱非线性二维半方法进行数值仿真,分析该控制方法的减摇控制效果。创新点:1.提出基于船舶运动预报和水动力预报的减摇方法,克服了控制时延对减摇效果的影响;2.基于弱非线性二维半方法进行船舶运动减摇数值仿真,验证了该方法能够实现良好的联合减摇控制效果。方法:1.在控制过程中基于极短期预报方法预报船舶运动姿态,并利用船舶运动方程预报水动力,将预报的水动力作为鳍角分配的依据;2.基于弱非线性二维半方法在时域内进行船舶运动减摇数值仿真,分析该控制方法在各种不同海况下的减摇控制效果。结论:1.弱非线性二维半方法在高速船舶的水动力预报中可以获得良好的效果;2.在各个不同海况下,本文提出的控制方法能够实现有效的联合减摇。

Prediction of added resistance of a ship in waves at low speed

This paper presents predictions of the added resistance of a ship in waves at a low speed according to the IMO minimum propulsion power requirement by a hybrid Taylor expansion boundary element method(TEBEM).The flow domain is divided into two parts:the inner domain and the outer domain.The first-order TEBEM with a simple Green function is used for the solution in the inner domain and the zero order TEBEM with a transient free surface Green function is used for the solution in the outer domain.The TEBEM is applied in the numerical prediction of the motions and the added resistance in waves for three new designed commercial ships.The numerical results are compared with those obtained from the seakeeping model tests.It is shown that the prediction of the ship motions and the added resistance in waves are in good agreement with the experimental results.The comparison also indicates that the accuracy of the motion estimation is crucial for the prediction of the wave added resistance.In general,the TEBEM enjoys a satisfactory accuracy and efficiency to predict the added resistance in waves at a low speed according to the IMO minimum propulsion power requirement.