水下无人作战系统装备现状及发展趋势

海军水下无人作战系统因其造价低廉、隐蔽性强、避免人员伤亡等诸多优点而得到大力发展,美国等国已制定各类水下无人作战系统发展规划并开发出便携型、轻型、重型和巨型等多种水下无人作战系统,并向着提高智能化、模块化和标准化程度、拓展多平台搭载使用能力等方向发展。为了应对威胁,我国也应从顶层规划水下无人作战体系发展路线,开发多样化的水下无人作战系统。     

基于扩张观测器的船舶动力定位系统反演滑模变结构控制

针对海洋平台船舶动力定位控制系统,结合反演滑模控制与扩张观测器的优势,提出一种基于扩张观测器的船舶动力定位反演滑模控制方法.考虑到系统存在未知外部干扰以及船舶模型参数不确定性的问题,将系统分为内环观测器和外环控制器分别设计,首先利用扩张观测器估计系统的未知状态及不确定项,然后在外环的反演滑模控制器中进行补偿,最后用Lyapunov方法证明系统的稳定性.通过船舶定点控制仿真实验表明,基于扩张状态观测器的反演滑模控制器使得船舶纵荡和横荡的位置及首摇角度逐渐保持在期望值,具有较强的鲁棒性和控制性,能够有效抑制传统滑模控制的抖振问题,有益于船舶工程应用.     

侧向风下航母甲板风涡流场的模拟研究

采用低马赫数假设下的气流运动控制方程组和湍流大涡模拟方法,研究在侧向来风条件下,航母甲板风涡流场的特点。在侧向来风时,航母前部甲板上方压强时均值、变化幅度与周期差异不大;后部甲板上方压强时均值较前半部分略有增加,变化幅度和周期均有所增大。     

船舶动力定位自适应滤波器设计

传统的陷波滤波器虽然能够很好的滤除一阶高频海浪波,但是滤波的同时也使得信号产生了相位滞后,在时域里面的表现就是信号的延时.卡尔曼滤波器虽然能够解决这一问题,但是其非常依赖于船舶模型.本文针对传统陷波滤波器的缺陷,使用了一种积分补偿型陷波滤波器,对传统的陷波滤波器进行改进.并以某拖轮为仿真对象进行仿真实验,其结果表明,该滤波器不但能够很好的滤除高频海浪波,还能够保持很好的相位特性.同时,递推的最小二乘估计(RLS)方法能够实时的估计出海浪的主导波频,使得陷波滤波器具有很好的自适应性.     

基于船模水池试验的船舶顺浪纯稳性损失计算扩展模式

船舶顺浪航行的纯稳性损失研究,已成为国际航海界和国际海事组织(IMO)关注的课题之一.在Ю.И.涅查耶夫根据28艘渔船和运输船船模水池试验的船舶顺浪纯稳性损失计算方法的基础上,提出了扩展模式,扩大了其适用范围,并给出了大长宽比(船长/船宽)舰艇纯稳性损失的算例,同时实现了该扩展模式的程序化,生成了实用化的软件.最后通过与CFD试验方法和一般理论计算法所得结果的对比,验证了该扩展模式计算结果的可信度.     

复杂外形潜水器的动力学建模

为建立复杂外形潜水器精确的动力学模型,并基于模型设计控制算法,本文以DOE HD2+2无人遥控潜水器(ROV)为对象,应用计算流体力学(CFD)粘流方法与面元法预测水动力系数.为提高计算速度,在保证计算精度的前提下,采用多面体网格,进行网格优化,减少了流体域的网格总数.由于ROV几何外形不对称,基于最小二乘法分段拟合了阻尼力/力矩与速度的曲线,建立了耦合的阻尼矩阵和附加质量矩阵.最后,基于CFD计算的水动力系数建立了Matlab Simulink动力学仿真模型,并通过水池操控实验对所建动力学模型进行了有效性验证.     

深海海山周围航船噪声建模与特性研究

本文以抛物方程模型为基础,结合声场的互易性,提出一种深海低频航船噪声建模方法,该方法将声源与接收点位置互换,大大降低了声场计算的运行次数和运行时间,基于该方法对深海海山周围的航船噪声进行计算和分析.研究结果表明:海山对声传播损失的影响取决于接收阵元与海山的位置关系以及海山的几何参数.由于海山的遮挡作用,海山附近航船噪声的水平指向性具有不均匀性,在有海山遮挡的方向噪声级明显低于无海山遮挡的方向,海山附近航船噪声的垂直指向性会出现多个峰值.此外,单个尖峰海山的遮挡对接收阵元处的航船噪声总级影响较小.     

The Bid-rent Land Use Model of the simple,efficient, elegant,and effective model of land use and transportation

Integrated land use/transportation forecasting models add significant policy and infrastructure alternatives analysis capabilities to the urban planning process. The financial, time, and staff requirements to develop these models has put them beyond the reach of most small to medium sized urban areas. This paper presents the land use allocation submodel of the Simple, Efficient, Elegant, and Effective model of land use and transportation (SE³M), an integrated land use and transportation forecasting model founded upon Economic Base Theory and Bid-rent Theory. The Bid-rent Land Use Model (BLUM) is an agent based, spatial competition model utilizing unique utility curves for willingness to pay and incomes for budget constrained abilities to pay for each agent. The model structure, estimation, calibration, implementation, and validation are presented. With a single year of land use data available, the validation approach used the Kappa Index of Agreement to spatially check model outputs against base year control data while controlling for agreement by chance. The U.S. territory of Guam is used as the case study/proof of concept implementation for this model framework. Once calibrated, BLUM could solve the spatial competition problem on Guam in less than two minutes of processing time with over 90% accuracy.     

Assessing the impact of reduced visibility on traffic crash risk using microscopic data and surrogate safety measures

Due to the difficulty of obtaining accurate real-time visibility and vehicle based traffic data at the same time, there are only few research studies that addressed the impact of reduced visibility on traffic crash risk. This research was conducted based on a new visibility detection system by mounting visibility sensor arrays combined with adaptive learning modules to provide more accurate visibility detections. The vehicle-based detector, Wavetronix SmartSensor HD, was installed at the same place to collect traffic data. Reduced visibility due to fog were selected and analyzed by comparing them with clear cases to identify the differences based on several surrogate measures of safety under different visibility classes. Moreover, vehicles were divided into different types and the vehicles in different lanes were compared in order to identify whether the impact of reduced visibility due to fog on traffic crash risk varies depending on vehicle types and lanes. Log-Inverse Gaussian regression modeling was then applied to explore the relationship between time to collision and visibility together with other traffic parameters. Based on the accurate visibility and traffic data collected by the new visibility and traffic detection system, it was concluded that reduced visibility would significantly increase the traffic crash risk especially rear-end crashes and the impact on crash risk was different for different vehicle types and for different lanes. The results would be helpful to understand the change in traffic crash risk and crash contributing factors under fog conditions. We suggest implementing the algorithms in real-time and augmenting it with ITS measures such as VSL and DMS to reduce crash risk.     

Direct formulation and algorithms for the probit-based stochastic user equilibrium traffic assignment problem

This paper proposes simple and direct formulation and algorithms for the probit-based stochastic user equilibrium traffic assignment problem. It is only necessary to account for random variables independent of link flows by performing a simple transformation of the perceived link travel time with a normal distribution. At every iteration of a Monte-Carlo simulation procedure, the values of the random variables are sampled based on their probability distributions, and then a regular deterministic user equilibrium assignment is carried out to produce link flows. The link flows produced at each iteration of the Monte-Carlo simulation are averaged to yield the final flow pattern. Two test networks demonstrate that the proposed algorithms and the traditional algorithm (the Method of Successive Averages) produce similar results and that the proposed algorithms can be extended to the computation of the case in which the random error term depends on measured travel time.