长江深水航道水下坝体抛石设备改造

长江下游河段施工区域地形异常复杂、水深和流速条件对抛石坝体形成非常不利。以长江南京以下12.5 m深水航道二期工程口岸直水道整治工程Ⅱ标段为依托,通过改造抛石设备、增加串筒约束构造来降低抛石高度、减小抛石漂移距的方法,减小外界条件对抛石落点的影响,从而达到控制块石落点的目的,实现了水下抛石精准定位。工程应用效果良好,在提高施工质量的同时降低了成本,为类似项目提供了借鉴。     

浅水中OSV锚泊定位分析研究

本文采用数值计算方法对浅水中海洋平台支持船(OSV)的锚泊定位性能开展研究.首先,基于三维频域势流理论,对一艘OSV不同水深的水动力性能开展分析,计算了水动力系数、运动幅值响应算子、一阶波浪力和二阶波浪力.由于浅水中非线性效应显著,本文采用中场公式计算了该OSV全二阶波浪力传递函数(Full Quadratic Transfer Function,简称全QTF).然后,本文对不同水深下锚泊系统的水平刚度开展了分析,计算了不同水深下锚泊系统的水平刚度,研究了水深对锚泊系统水平刚度的影响.最后,采用准动态方法对不同水深下的OSV和锚泊系统开展时域分析,研究了水深对船体运动性能和锚索张力的影响.     

舰载机试飞数据的移动基准区间与牛顿插值处理

分析飞行试验数据具有数据量大,需分段加载和截取的特点,针对试飞数据预处理过程中常规全局统计误差分析方法有时难以满足要求的问题,建立移动基准区间和牛顿插值相结合的误差修正模型,提出移动基准区间牛顿插方法,并应用于飞行试验数据处理中,最后通过实例验证其有效性.     

智能船舶研发风险分析与控制

针对智能船舶研发的风险问题,在介绍智能船舶的概念及智能船舶特点的基础上,通过系统分析智能船舶研发的各种风险,着重从技术和财务2个方面分析风险的因素,提出风险控制的相关对策和措施,为我国企业研发智能船舶进行风险控制提供参考.     

我国海洋生态环境损害程度评价技术发展现状

本文通过对目前海洋生态环境的判定技术的综合分析,按海洋污染生态毒性损害、海洋污染对渔业资源的损害以及涉海工程对海洋生态环境损害三个方面入手,介绍了国内外的海洋生态环境损害程度评价技术的发展现状,并指出我国相关研究中存在的不足。     

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.     

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.     

智能船舶发展现状及我国发展策略研究

近年来,智能船舶的发展呈加速趋势,智能船舶已成为未来船舶发展的主要方向.本文对当前国内外智能船舶发展现状进行系统梳理与比较分析,为我国智能船舶的发展提出若干建议.     

Bicycle mode share in China: a city-level analysis of long term trends

In the past 15 years, cities in China have experienced big changes in socioeconomic and traffic conditions, resulting in a long term change in bicycle use. This study aims to quantify the changes in bicycle mode share in Chinese cities and explore the potential causes. Based on data from 51 cities, it is found that bicycle mode share at the city level decreased gradually in the past. Conventional bicycle mode share decreased with a rate of 3 % per year, but electric bicycle mode share increased with a rate of 2 % per year. The correlations between city features such as demographics and built environments and bicycle mode share at different city sizes are compared. The generalized linear models are estimated to relate the changes in the share of different trip modes to various city-level factors. The results show that the bicycle mode share in a city is impacted by factors including city area size, population density, number of cars, percentage of local road mileage among all roads, and trip purpose. Possible reasons for the changes in bicycle uses in Chinese cities are explored and policy implications are discussed.     

Isolating high-priority metro and feeder bus transfers using smart card data

Fixed-rail metro (or ‘subway’) infrastructure is generally unable to provide access to all parts of the city grid. Consequently, feeder bus lines are an integral component of urban mass transit systems. While passengers prefer a seamless transfer between these two distinct transportation services, each service’s operations are subject to a different set of factors that contribute to metro-bus transfer delay. Previous attempts to understand transfer delay were limited by the availability of tools to measure the time and cost associated with passengers’ transfer experience. This paper uses data from smart card systems, an emerging technology that automatically collects passenger trip data, to understand transfer delay. The primary objective of this study is to use smart card data to derive a reproducible methodology that isolates high priority transfer points between the metro system and its feeder-bus systems. The paper outlines a methodology to identify transfer transactions in the smart card dataset, estimate bus headways without the aid of geographic location information, estimate three components of the total transfer time (walking time, waiting time, and delay time), and isolate high-priority transfer pairs. The paper uses smart card data from Nanjing, China as a case study. The results isolate eight high priority metro-bus transfer pairs in the Nanjing metro system and finally, offers several targeted measures to improve transfer efficiency.