舰船电子元器件自主可控现状与发展需求研究

近年来,我国信息化关键软硬件技术得到了长足发展,特别是基础电子元器件性能有了大幅度提升.然而,在信息化相关的电子元器件技术和产品上与国外还存在较大差距,制约了装备的国产化率和自主可控能力水平的进一步提升.本文分析舰船装备领域基础电子元器件的发展现状,并提出下一步的发展需求建议以及确保基础电子元器件自主可控的具体措施.     

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.     

基于高雷诺数的并联双圆柱绕流研究

文章采用基于边界瞬时涡量守候的拉格朗日方法(IVCBC),结合并列双圆柱的特点,建立了双圆柱绕流数值计算模型。对高雷诺数下Re=6×10~4,间隙率为T/D=1.1~7的并联圆柱双圆柱二维绕流特性进行了研究。提出了双圆柱间隙中点的速度区别宽窄尾流的新方法。分别讨论了流体力系数随间距增加的特点,脉动流体力的特点,尾流特征以及斯托哈尔数特征。研究发现:区别宽窄尾流的新方法是可靠的;在双圆柱尾流附近有五种尾流模型存在;同时发现了在宽窄尾流的频率,存在一个中间频率。     

东海涌浪环境下大型起重船吊装组块耦合运动响应数值模拟研究

我国东海海洋环境复杂,经常出现小波高、长周期的涌浪.长周期涌对系泊大型起重船吊装海洋平台上部组块影响比较大,尽管涌的波高较小,但是,吊物组块运动幅度明显比同等波高海况时的要大,严重影响了海洋平台的安装施工效率和进度,甚至威胁作业安全.本文采用水动力势流软件,建立系泊-大型起重船(包括吊臂)-索具-大型组块吊物的耦合运动模型,研究复杂涌浪环境下耦合系统运动响应特性及其机理,并开展了参数敏感性分析,讨论对耦合响应影响因素.最后,对东海涌浪情况下起重安装施工,提出了降低吊装组块运动响应的建议措施.     

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。     

基于相关性模型的舰船系统测试性建模与分析

本文提出一种基于相关性模型的舰船系统级产品的测试性建模与分析方法.该方法通过建立产品任务模型、相关性图示模型等,利用一阶相关性列矢量法求解产品的相关性数学模型,进而建立产品诊断树和进行测试性预计,并为优化产品诊断策略提供建议.同时,根据舰用燃气轮机滑油系统组成和任务特征,建立其典型任务模型并进行精简,并在此基础上进行测试性建模、诊断树建立、测试性预计以及诊断策略优化等工作,为舰船系统级产品的测试性建模、分析和诊断策略研究提供新思路和手段.     

营运船舶航行性能和海洋环境监测平台开发验证

EEDI是衡量船舶能效水平的重要指标.由于试验条件限制,目前主要还是依靠模型试验结果对交船测试进行修正换算得到.上海船舶运输科学研究所自主研发了航行性能和海洋环境监测平台,可对营运船舶开展长期跟踪监测,实时收集船舶营运阶段的航行环境和性能参数,通过自动识别航行状态,划分海区、海况和船舶载况等因素对于船舶功率与航速的影响,可获得营运船舶实际EEDI指标,提高EEDI实船验证结果的准确性.监测平台在某万箱级集装箱船进行相关验证,并已展开长期监测.     

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.     

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.     

Impact of regional population density on walking behavior

Land use can influence walking (measured by the number of steps) and so the health of people. This paper presents the result of empirical research on the impact of regional population densities (inhabitants per inhabitable area) on the number of steps (all steps, both outdoors and indoors). With data collected from almost 11,000 respondents in 148 Japanese regions, we estimate polynomial regression models, the total number of steps being the dependent variable and densities being the main independent variable. Regional population density significantly affects the number of steps after controlling for individual and household attributes. The estimated population density that maximizes the number of steps is around 11,000?persons/km². Increasing densities, up to levels of around 11,000?inhabitants/km², could increase walking and consequently the health of inhabitants. The population density elasticity of the number of steps is 0.046–0.049 in a simple log linear regression model without a peak.