循环式燃油系统的仿真和优化

本又研究了一种适合劣质燃油（重油）的新型循环式燃油系统（一泵二嘴四阀），并建立了描述新型喷油器的四区模型，以及用于燃油分配器和新型喷油泵的仿真模型。仿真结果与试验结果较为吻合。本文还进行了不同功率点变型方案的仿真研究和结构参数的优化设计分析，以满足不同船舶的需要。     

Ship inspection support system using a product model

 Recently, the significance of ship inspections has been increasingly recognized because sea pollution and safety problems are occurring more and more frequently. However, current ship inspections rely on the experience of the workers. Therefore, it is difficult to understand, and hence to improve, the state of ship inspections. In this paper, ship inspection is directed into three stages (plan, do, and check), and the configurations of a total system to support ship inspections are discussed. A prototype system for the “plan” and “do” stages is developed. This is realized by organizing the information that relates to inspection, and defining data models for damage and inspection states. Then the proposed system is integrated with a shipbuilding computer integrated manufacturing (CIM) system so that the ship's structural information can be used effectively. In addition, functions to calculate the damage-finding probability, and functions to generate information about damage and the inspection state are introduced. Therefore, in the planning stage, as inspector can execute a virtual ship inspection, and then the damage-finding probability of each hull part and oversight areas are calculated automatically. Further, by carrying this system into an inspection, an inspector can generate damage information and inspection information simply and easily. Some examples of the proposed system are shown at the end of the paper. Received: November 12, 2001 / Accepted: January 30, 2002     

新型船舶运动控制平台及海上试验

研制出一艘以水动力学相似准则缩尺的无人驾驶遥控模型船，模型船装有PC／104为主控计算机的船舶控制器，模型船由岸上主PC机遥控，用Honeywell公司的HMR3000碰罗经测量航导，用差分GPS系统定位，自主控制和推进，该遥控篡自治船舶运动控制已经进行了两次海上试验并取得成功，本文介绍该平台的系统设计，控制系统硬件和软件和海上试验经。     

汽车防抱制动系统的自寻最优控制

通过分析车轮制动的工作原理，提出了汽车防抱制动系统的自寻最优控制方法。仿真结果表明，在不同的路况下，防抱制动系统的自寻最优控制取得了满意的效果。文中提出的自寻最优控制方法相对以往的控制方法更为简单，更适合于实际应用。     

汽车碰撞散落物再现模型研究

选取交通事故现场遗留的典型散落物作为试验对象,制作散落物承载装置并模拟真实环境下的车辆碰撞过程,利用VC3000加速计实时计测试验车相关运行参数,在干燥沥青路面进行散落物抛撒试验,深入分析散落物在地面的分布形态,利用ADAMS仿真分析散落物与车辆之间的相对运动过程,探讨路面散落物分布场的特征参数与碰撞车速的关系。     

中高速列车共线运行的仿真研究

以京沪高速为背景,对中高速列车共线运行仿真问题进行探讨。分别建立单列车运行模型和多列车共线运行模型。单列车运行模型全面考虑了列车物理特性、线路条件、列车受力情况以及运行控制过程。多列车模型在上述基础上,附加了共线运行不同速度列车间的相互影响,对列车间距控制和避让进行了重点考虑,研究多列车共线运行时的列车间距控制策略和避让策略。用VisualC 6 0进行了中高速列车共线运行的软件实现。仿真计算结果表明,该软件能较好模拟多列车共线运行情况,可作为列车调度系统中负责列车运行模拟的子系统。     

竖向预应力作用效果的数值模拟与预应力损失的试验研究

对箱梁竖向预应力筋张拉引起的混凝土竖向应力和螺纹钢筋的应力进行了有限元计算和现场测试分析,测试结果表明预应力损失离散性很大,而且预应力损失可能高达50%.这是由于箱梁的高度有限,竖向预应力筋的长度都比较短,因而在达到张拉控制应力时高强精轧螺纹粗钢筋的伸长量有限.目前的竖向预应力锚固技术尚存在不足,在锚固时稍有不慎造成钢筋回缩量偏大,很容易造成预应力损失.     

高速列车与铁路简支组合梁动力相互作用仿真分析

针对中小跨度上承式钢板梁桥在提速时横向振幅过大的问题,提出将钢板梁桥改造成组合桥梁。应用MSC/DYTRAN大型软件对改造后的32m简支组合梁结构进行桥梁动力特性及列车走行性分析。结果表明,当运行速度在140~220km.h-1时,机车车辆的乘客乘座舒适度满足良的标准,改造后简支组合梁结构满足高速旅客列车速度小于220km.h-1的走行性要求。     

水下机器人运动控制与仿真的数学模型

本文首先确定了水下机器人六自由度空间运动模型，为了便于在控制与仿真中应用，本文借助matlab平台，将水下机器人的六个自由度的方程转换为矩阵乘形式，然后结合水下机器人的环境仿真，推力器仿真，舵翼仿真，建立了水下机器人六自由度运动记真器。最后用该仿真器进行了运动仿真，仿真结果与海上试验吻合得很好，表明该仿真系统是符合实际的，该仿真系统采用一种普遍实用的数学模，精度较高，适用于任何类型的水下机器人，对研究水下机器人操纵与控制有很大现实意义。     

Simulation of the mean zero-up-crossing wave period using artificial neural networks trained with a simulated annealing algorithm

The aim of this work was to develop a predictive model to forecast the mean zero-up-crossing wave periods (T _z ) for 3-hourly sea states at a location in the Pacific using artificial neural networks (ANNs). Seven multilayer ANNs were trained with a simulated annealing algorithm. The output of each trained ANN was used to estimate each of the seven parameters of a new distribution called the hepta-parameter spline proposed for the conditional distribution of T _z , given some mean zero-up-crossing wave periods and significant wave heights. After estimating the parameters of the distribution, the model was used to simulate and predict future values of T _z . Forecasting a sea state and developing the joint distribution of sea state characteristics with the help of the simulated characteristics are also discussed in this article.