舰载弹库泄压排导技术研究

通过对弹药发生爆炸时的内部压力流场进行分析,并分别针对弹药爆炸及导弹意外点火时产生的爆压进行探讨,提出安全有效的泄压排导措施;对泄压排导装置工作时的壳体强度、压盘受力情况进行研究,并给出具体的计算与校核方法,为弹库泄压排导设计提供重要理论依据与技术支撑.     

基于磁流变弹性体的船舶轴系纵振动力吸振器的实验研究

磁流变弹性体是一种新型的智能材料,由微米级的羰基铁粉和聚合物合成.由于它具有弹性模量可调、无需封装、稳定性好、响应快等优点,已被广泛应用于机械振动控制等领域.文中针对船舶推进轴系纵振动力学特性,提出一种固有频率可调的磁流变弹性体动力吸振器用于轴系纵振控制.首先理论分析了安装动力吸振器的推进轴系的动力学模型,其次对动力吸振器进行了移频特性试验,并在1:4的船舶轴系缩比模型上进行了变转速工况下吸振效果试验.实验结果表明,该吸振器具有12.3 Hz的移频范围,并且在不同轴系工作转速下相比于被动式吸振器均有更好的吸振效果.     

超声冲击处理对高强钢焊接接头残余应力影响的数值模拟

超声冲击处理(UIT)是一种有效的焊后改善焊接接头疲劳性能的工艺措施,其借助机械撞击和超声振动的共同作用,使焊趾表面产生塑性变形从而引入有益的压缩残余应力。为评价UIT技术对焊接接头残余应力的影响,该文提出了一套新的数值分析方法,包括焊接数值模拟及随后的超声冲击处理过程的动态弹塑性有限元分析。在有限元模型中考虑了实际的工艺参数和超声促成的材料软化效应。以船用高强钢AH36非承载十字焊接接头为研究对象,将预测的超声冲击处理前后的残余应力分布与实验结果进行对比,两者有较好的吻合。在此基础上,探讨了静态预载荷对超声冲击处理态残余应力再分布的影响。     

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.     

国外舰艇综合电力系统研究综述

舰艇综合电力系统实现了全舰能源的综合利用,是舰艇平台由机械化向电气化和信息化发展的必由之路,代表现代舰艇动力平台的发展方向.本文通过对国外舰艇综合电力系统应用现状、技术状态、军事意义及未来发展趋势进行分析梳理,供相关人员参考.     

Airline energy efficiency measures using the Virtual Frontier Network RAM with weak disposability

In this paper, airline energy efficiency is divided into three stages: the operations stage, the services stage and the sales stage. Greenhouse gas emissions are treated as an undesirable output of the services stage. This new three-stage strategic operating framework is a modification of existing models. A new model, Virtual Frontier Network Range Adjusted Measure with weak disposability, is proposed to evaluate the efficiencies of 22 international airlines, from 2008 to 2012. The results show that the new model can establish more reasonable rankings and confirm new benchmarking airlines and that inclusion in the European Union’s Emissions Trading Scheme has had little influence on the improvement of airline energy efficiency.     

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.     

基于AIGA-WLSSVM的埋地管道腐蚀速率预测方法

为了降低埋地管道腐蚀影响因素之间的复杂相关性,提高腐蚀预测精度,文中提出一种基于自适应免疫遗传算法-加权最小二乘支持向量机(AIGA-WLSSVM)的埋地管道腐蚀速率预测建模方法,并采用AIGA优化模型参数,进一步提高模型的学习能力和稳定性。最后通过实例分析验证了AIGA-WLSSVM建模方法在埋地管道腐蚀速率预测中的可行性和有效性,为埋地管道的检修与更换提供参考。