大阪号油轮在浅水,有限航速下的操纵水动力计算

利用浅水有限航速下操纵船体的水动力计算方法计算了大阪号油轮的操纵运动线性水动力导数，将计算结果与试验结果进行了比较，结果是令人满意的。     

基于神经网络的船舶航向自适应PID控制

详细分析基于单神经元的自适应PID控制算法,并推导了为改进其应用上的不足,将自适应PSD控制器中递推计算增益K的方法应用到单神经元的自适应 PID控制,构成具有自动调整增益K值的单神经元自适应PID控制器的学习算法.将控制算法应用到船舶航向控制系统,仿真结果显示了该方法的有效性.     

船舶航向模糊控制及仿真研究

根据船舶操纵控制过程中,存在非线性、慢时变、复杂干扰的特点,设计了一个带模糊积分的船舶航向模糊控制器,使船舶在干扰变化情况下,模糊控制不仅能较好地实现航向保持,而且能获得较好的操纵性能;仿真结果表明,带模糊积分的船舶航向模糊控制器的控制比常规PID控制具有更强的环境适应性.     

基于NURBS的船舶型线设计程序EHULL

以非均匀有理B样条NURBS为基础,通过交互式手段实现船舶型线的三维动态设计和实体造型,程序具有升阶、分割、节点去除等功能,可以计算曲面的高斯曲率、获得各种剖面的形状和线型图、肋骨型线图;可生成各种二次曲面、计算船舶静水力。     

小水线面双体船粘性流数值模拟

利用商业软件FLUENT对一小水线面双体船(SWATH)的粘性绕流进行数值模拟,得到了不同航速下的三维粘性流场和粘性阻力,通过对计算结果的分析、比较,验证了FLUENT用于预报小水线面双体船粘性阻力和伴流分布的有效性和实用性。     

Prediction of hydrodynamic forces on a moored ship induced by a passing ship in shallow water using a high-order panel method

A three-dimensional high-order panel method based on non-uniform rational B-spline (NURBS) is developed for predicting the hydrodynamic interaction forces on a moored ship induced by a passing ship in shallow water. An NURBS surface is used to precisely represent the hull geometry. Velocity potential on the hull surface is described by B-spline after the source density distribution on the boundary surface is determined. A collocation approach is applied to the boundary integral equation discretization. Under the assumption of low passing speed, the effect of free surface elevation is neglected in the numerical calculation, and infinite image method is used to deal with the finite water depth effect. The time stepping method is used to solve the velocity potential at each time step. Detailed convergence study with respect to time step, panel size and Green function is undertaken. The present results of hydrodynamic forces are compared with those obtained by slender-body theory to show the validity of the proposed numerical method. Calculations are conducted for different water depths and lateral distances between ships, and the detail results are presented to demonstrate the effects of these factors.     

用RBF网络学习船舶操纵运动的动态特性

提出了利用径向基（ＲＢＦ）神经网络的非线性映射能力,来学习船舶操纵动态特性,通过大量的仿真实验证明,用ＲＢＦ网络学习船舶操纵动态特性,在学习速度、预报误差待经常用的ＢＰ网络要优越得多。     

多开边界群岛海域溢油模拟的水动力模式

建立了一个多开边界群岛海域溢油模拟的三维水动力模式,并在舟山定普港域作了模拟和预报试验。模式采用高分辨的水平曲线正交网格和２．５阶湍流闭合模型,通过有限差分隐式／半隐式求解具有初、边值条件的三维原始动力方程组。初步试验表明,模式重视了港域内许多重要的流动力学特征,能模拟或预报海域内三维潮流、风生流及其相互作用,并为溢油模拟提供实时流场。