Research on Bulbous Bow Optimization Based on the Improved PSO Algorithm

In order to reduce the total resistance of a hull, an optimization framework for the bulbous bow optimization was presented. The total resistance in calm water was selected as the objective function, and the overset mesh technique was used for mesh generation. RANS method was used to calculate the total resistance of the hull. In order to improve the efficiency and smoothness of the geometric reconstruction, the arbitrary shape deformation (ASD) technique was introduced to change the shape of the bulbous bow. To improve the global search ability of the particle swarm optimization (PSO) algorithm, an improved particle swarm optimization (IPSO) algorithm was proposed to set up the optimization model. After a series of optimization analyses, the optimal hull form was found. It can be concluded that the simulation based design framework built in this paper is a promising method for bulbous bow optimization.     

BP神经网络精度估计及其在海洋油气资源预测中的应用

在对BP算法进行深入分析的基础上,将测量数据处理与误差理论中的精度评定方法应用到BP神经网络的精度估计中,通过分别计算BP神经网络学习训练过程及预测过程的输出层中误差,实现对神经网络模型的精度评定。最后以海洋油气资源预测为例,结合实测资料建立了BP神经网络预测模型并分别进行了学习训练过程及预测过程的精度评定,以期为神经网络模型结构的优化设计提供有效参考,为提高神经网络模型的适用性提供科学依据。     

The Relationship between Propagation Time and Sound Velocity Profile for Positioning Seafloor Reference Points

This paper focuses on the relationship between the propagation time and the integral of the sound velocity profile (SVP) with respect to depth (SVP area for short) for positioning seafloor reference points. We proved a linear relationship between the propagation time and the SVP area and defined its mathematical expression (ST law). We showed in three simulations of possible variations in SVPs (random errors, internal waves, or a combination of both) that this ST law is verified. Using this new law in a simulated experiment, the ranging residuals due to sound velocity change through time are significantly improved. With this method, monitoring the SVP while acquiring travel times to a submerged transponder can significantly reduce the positioning errors of the transponder.     

Minimal Time Ship Routing Using IRS-P4 (MSMR) Analyzed Wind Fields

Minimal time ship routing is studied between Mumbai port (India) to Mombasa port (Kenya) using model hindcast wave climate over the Arabian Sea. With the launch of IRS-P4 (OCEANSAT-I), it became possible now to carry out routine wave hindcasting over the Indian Ocean. The MSMR channel of the satellite gives scalar wind, which is analyzed at NCMRWF, India, for converting to vector winds. The same is used as input to third-generation spectral wave model WAM for regional grid system for simulating the rough weather period of July 2000. This simulated wave climate formed the basis for computing effective ship velocity in the irregular seaway. This study gives a quantitative estimation of change in ship velocity in the open Indian Ocean for a bulk carrier. The minimal time path is charted using Dijkstra's algorithm for optimum route voyage. The optimum track information has broad scope for obtaining a safer route, least time route by avoiding delay in schedule with minimum fuel consumption.     

CUBE算法及其在多波束数据处理中的应用

阐述了一种基于表面生成的多波束数据处理方法——CUBE(Combined Uncertainty and Bathymetry Estimator)算法,用该方法可以对观测区域网格节点"真实"水深及相关误差进行估计。与从测量水深中选择出"最佳"数据的手工交互方式的多波束数据编辑手段不同,CUBE算法具有很强的抗差性和较高的效率,适合于实时多波束数据处理。对南海某测区多波束数据处理结果表明,在没有人工干预的情况下,利用CUBE算法去噪生成的海底DTM图与手工编辑生成的相当吻合。CUBE算法和手工编辑方法综合对比得出,CUBE算法能够很好地保留水深地形细节,在计算效率、误差评估、实时处理等方面比手工编辑方法具有较大的优势。     

Modal Identification of Offshore Platforms Using Statistical Method Based on ERA

Identification of modal parameters of a linear structure with output-only measurements has received much attention over the past decodes. In the paper, the Natural Excitation Technique (NEXT) is used for acquisition of the impulse signals from the structural responses. Then Eigensystem Realization Algorithm (ERA) is utilized for modal identification.For disregarding the fictitious ‘computational modes’, a procedure, Statistically Averaging Modal Frequency Method (SAMFM), is developed to distinguish the true modes from noise modes, and to improve the precision of the identified modal frequencies of the structure. An offshore platform is modeled with the finite element method. The theoretical modal parameters are obtained for a comparison with the identified values. The dynamic responses of the platform under random wave loading are computed for providing the output signals used for identification with ERA. Results of simulation demonstrate that the proposed method can determine the system modal frequency with high precision.     

Development of a Neural Network Algorithm for Retrieving Concentrations of Chlorophyll, Suspended Matter and Yellow Substance from Radiance Data of the Ocean Color and Temperature Scanner

An algorithm is presented to retrieve the concentrations of chlorophyll a, suspended pariclulate matter and yellow substance from normalized water-leaving radiances of the Ocean Color and Temperature Sensor (OCTS) of the Advanced Earth Observing Satellite (ADEOS). It is based on a neural network (NN) algorithm, which is used for the rapid inversion of a radiative transfer procedure with the goal of retrieving not only the concentrations of chlorophyll a but also the two other components that determine the water-leaving radiance spectrum. The NN algorithm was tested using the NASA's SeaBAM (SeaWiFS Bio-Optical Mini-Workshop) test data set and applied to ADEOS/OCTS data of the Northwest Pacific in the region off Sanriku, Japan. The root-mean-square error between chlorophyll a concentrations derived from the SeaBAM reflectance data and the chlorophyll a measurements is 0.62. The retrieved chlorophyll a concentrations of the OCTS data were compared with the corresponding distribution obtained by the standard OCTS algorithm. The concentrations and distribution patterns from both algorithms match for open ocean areas. Since there are no standard OCTS products available for yellow substance and suspended matter and no in situ measurements available for validation, the result of the retrieval by the NN for these two variables could only be assessed by a general knowledge of their concentrations and distribution patterns. This revised version was published online in July 2006 with corrections to the Cover Date.     

一种基于道路网分层的最短路径算法

D ijkstra算法是求解最短路径的经典算法,A*是目前最流行的启发式搜索算法,分析了这两种算法的搜索空间和时间复杂度。在此基础上,提出了一种基于道路网分层最短路径算法。实验证明:该算法是一种效率好、实用性强的最短路径算法。     

关于矩阵方程A~TX+X~TA=B的极小范数解

作者讨论矩阵方程 ATX+ XTA=B。该方程在 Hamilton力学研究中有用。首先利用L yapunov方程证明了极小 Frobenius范数解的存在性和惟一性。然后用奇异值分解给出了求解最小范数解的一种方法。最后讨论极小范数解的向前扰动分析和最佳向后扰动分析     

含初始缺陷海底管道侧向屈曲临界力的参数解

未埋设的海底管道在高温高压运行条件下可能发生侧向屈曲,情况严重时影响海底管道的结构安全。侧向屈曲临界力作为判定海底管道发生侧向屈曲的重要依据,主要影响因素有初始缺陷、管土相互作用等。现有关于侧向屈曲临界力的公式并未考虑管土相互作用、缺陷不平直度和管道自身材料特性对侧向屈曲临界力的综合影响。建立含有通用几何初始缺陷海底管道的数值模型,使用Riks算法进行参数分析以研究极限侧向土壤阻力、管道缺陷不平直度和截面几何尺寸对海底管道侧向屈曲的具体影响。基于量纲分析法和多元线性回归,推导出海底管道侧向屈曲临界力关于上述3个影响参数的一般公式,并对该公式进行了检验,结果表明文中推导的公式在参数涵盖的研究范围内有效。