固-液旋流分离器结构优化模拟研究

采用计算流体力学方法与流体动力学分析软件Fluent,探讨了固-液旋流分离器的溢流口直径、锥角、圆柱段长度和入口直径等主要结构参数对其颗粒溢流率的影响,并在此基础上进行结构参数的优化。结果表明,锥角、圆柱段长度和入口直径过大或过小都不利于旋流分离器的固液分离,均存在一个最佳值。对于主直径为75 mm的单锥双入口固-液旋流分离器,最佳圆柱段长度为87.0 mm,最佳入口直径为16.0 mm,最佳溢流口直径为16.5 mm,最佳锥角为6.0°。     

装备体系结构优化可行方案空间构建方法

针对装备体系结构方案数量规模较大及传统构建方法效率较低的问题,以单一费用约束条件下的装备体系结构优化问题为例,提出了一种可行空间构建的新方法,试图缩小体系成员的遍历范围,减少运算量,提高体系结构可行方案空间的构建效率。最后,利用Matlab软件对新算法进行数值模拟与仿真,并与传统方法进行了比较,结果表明:新方法的计算效率得到了明显提高。     

基于变异离散粒子群的协同空战攻击决策算法

为了提高智能协同空战攻击决策算法性能,将变异策略引入到DPSO(Discrete Particle Swarm Optimization)协同空战攻击决策算法中,提出了一种新的基于变异离散粒子群(Mutation Discrete Particle Swarm Optimization,MDPSO)的协同空战攻击决策算法。基于典型空战想定背景,仿真验证了算法的有效性。采用对比实验方法,基于准确性、可靠性和快速性等关键性能指标,分析比较了基于MDPSO协同空战攻击决策算法与多种智能决策算法,验证了基于MDPSO的协同空战攻击决策算法有着较好的综合性能。     

小波神经网络UCAV飞行控制系统

针对采用H∞控制设计方法需求解难度很大的偏微分方程,而导致工程实现难度大的问题,提出了采用小波神经网络进行无人攻击机(UCAV)飞行控制系统设计的方法,该方法集小波变换和神经网络的优点于一身,简化了网络训练,避免了系统达到局部最优解,使得系统具有更好的逼近精度。通过仿真实验表明,利用小波神经网络进行UCAV控制律设计,使系统具有较好的跟踪性和鲁棒性,避免了精确模型的建立,便于分析系统的稳定性。     

基于遗传算法的涡轮增压器叶轮优化设计

提出了一种基于遗传优化理论的涡轮增压器叶轮的优化设计方法,论述了以涡轮增压器叶轮能量损失最小为目标函数,以叶轮叶片进口角、进口直径、进口宽度、出口直径、叶片数、出口角为设计变量的涡轮增压器叶轮的优化设计模型及优化计算的方法,数值计算表明,这种算法可以方便地求得具有最小涡轮损失的涡轮叶形参数.     

多级可修备件库存的生灭过程建模与优化

针对VARI-METRIC模型在低可用度下结果不准确的问题,建立基于生灭过程的任意等级、任意层级可修件库存优化模型。通过对各级站点、各类备件需求率与到达率的预测,对每个部件建立其生灭过程模型,并提出基于生灭过程的装备可用度计算方法。以整个保障系统的装备可用度为约束指标,以备件总购置费最低为目标,利用边际算法得到最优备件配置方案,并建立仿真模型对所得优化方案进行评估与调整。结合算例,以仿真结果作为检验标准,选取权威的VMETRIC软件与该解析模型在优化性能、计算精度及适用性上进行对比和说明。结果表明,无论是解析模型还是VMETRIC软件,均存在一定的适用范围,而采用解析与仿真相结合的方法无疑具有更强的适应性。     

Optimal service and arrival rates in Jackson queueing networks

In this paper we present an algorithm for solving a class of queueing network design problems. Specifically, we focus on determining both service and arrival rates in an open Jackson network of queueing stations. This class of problems has been widely studied and used in a variety of applications, but not well solved due to the difficulty of the resulting optimization problems. As an example, consider the classic application in computer network design which involves determining the minimum cost line capacities and flow assignments while satisfying a queueing performance measure such as an upper limit on transmission delay. Other application areas requiring the selection of both service and arrival rates in a network of queues include the design of communication, manufacturing, and health care systems. These applications yield optimization problems that are difficult to solve because typically they are nonconvex, which means they may have many locally optimal solutions that are not necessarily globally optimal. Therefore, to obtain a globally optimal solution, we develop an efficient branch and bound algorithm that takes advantage of the problem structure. Computational testing on randomly generated problems and actual problems from a health care organization indicate that the algorithm is able to solve realistic sized problems in reasonable computing time on a laptop computer. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 1–17, 2000     

Optimal (τ, T) opportunistic maintenance of a k‐out‐of‐n:G system with imperfect PM and partial failure

The opportunistic maintenance of a k‐out‐of‐n:G system with imperfect preventive maintenance (PM) is studied in this paper, where partial failure is allowed. In many applications, the optimal maintenance actions for one component often depend on the states of the other components and system reliability requirements. Two new (τ, T) opportunistic maintenance models with the consideration of reliability requirements are proposed. In these two models, only minimal repairs are performed on failed components before time τ and the corrective maintenance (CM) of all failed components are combined with PM of all functioning but deteriorated components after τ; if the system survives to time T without perfect maintenance, it will be subject to PM at time T. Considering maintenance time, asymptotic system cost rate and availability are derived. The results obtained generalize and unify some previous research in this area. Application to aircraft engine maintenance is presented. © 2000 John Wiley & Sons;, Inc. Naval Research Logistics 47: 223–239, 2000     

一类非线性问题的数值分析

利用Ｌａｐｌａｃｅ方程的基本解,将变系数非齐次Ｈｅｌｍｈｏｌｔｚ偏微分方程的边值问题化为积分方程问题。再用边界无法进行离散,并对区域结点及边界结点的方程耦合求解。文末算例表明本文方法能够达到较高精度。     

非线性干扰观测器的高超声速飞行器自适应反演控制

针对高超声速飞行器参数不确定弹性体模型,提出了一种基于非线性干扰观测器的自适应反演控制器设计方法。将曲线拟合模型表示为严格反馈形式,采用反演方法设计控制器。采用动态面方法获取虚拟控制量的导数,避免了传统反演控制"微分项膨胀"问题。为了增强控制器的鲁棒性,基于二阶跟踪-微分器设计了一种新型非线性干扰观测器,以此对模型不确定项进行自适应估计和补偿。仿真结果表明,控制器对模型不确定性和气动弹性影响具有强鲁棒性,且能实现对速度和高度参考指令的稳定跟踪。