基于灰色关联分析的航空装备技术保障能力评价模型

航空装备技术保障能力是组成航空兵战斗力的基本要素之一,其能力的高低直接影响到航空装备保障任务完成质量的优劣,因此对航空装备技术保障能力进行科学评价具有重要意义.在现有研究的基础上建立了航空装备技术保障能力评价指标体系,基于灰色关联分析方法提出了指标权重的确定方法,并利用灰色关联分析思想构建出航空装备技术保障能力评价模型,为航空装备技术保障能力评价提供量化分析模型,拓展了航空装备技术保障能力评价模型体系.     

基于蒙特卡洛算法的航空兵场站装备广义维修过程研究

研究了适用于航空兵场站可修装备在多级备件、(s-1,s)库存下的广义维修过程解析模型。基于Monte Carlo算法,迭代产生大量样本数据,经过拟合发现该维修过程依分布收敛于一对数正态分布;再针对该样本分别以OLS(最小二乘),ML(极大似然)估计进行参数推断,得到了其稳态分布函数,通过了拟合优度检验。最后解出了该情况下装备的稳态维修度,稳态可用度等参数。对比simlox模型对该装备的评估结果,数据吻合程度较为理想。     

基于战役的多机种战伤备件需求模型

为了合理储备战时航材备件,通过分析战时故障备件的需求特点,改进了传统的单机故障备件需求模型.根据多机种协同作战任务的不同,引入备件工作运行比的概念,建立了基于作战任务的多机种故障备件需求模型.为解决多机种协同作战时的保障资源配置问题提供了思路和方法.     

军用机场四站保障效能评估方法研究

通过分析四站保障的影响因素,提出军用机场四站保障指标体系构建方法,运用系统分析法和Delphi法建立了四站保障指标体系,并形成军用机场四站保障效能评估方法,运用可能一满意度及层次分析等方法建立了军用机场四站保障效能评估模型.     

基于灰色系统理论的空军装备维修保障费用预测模型

随着空军武器装备的迅猛发展,维修保障在装备战斗力形成和发挥中的地位与作用越来越重要.运用灰色系统理论,科学确定装备维修保障需求,使维修保障系统建设与武器装备发展需求相协调,维修保障能力与装备作战需要相适应,不断满足现代高技术条件下军事斗争准备对维修保障的需求.     

基于TRNSYS的飞机空调保障装备送风特性仿真研究

针对飞机地面空调保障时飞机内部出现的结露问题,首先理论分析了飞机地面空调保障装备空调系统;其次利用TRNSYS软件建立飞机地面空调保障装备空调系统的仿真模型,对飞机地面空调保障装备的送风含湿量、送风温度、送风风量和通风时间进行分析,最后讨论了快速、高效的送风状态,为提高飞机地面空调保障效率作理论支撑.     

基于绩效保障模式的可修备件保障系统运营管理策略

基于绩效保障模式,设计了一个由备件仓库和维修车间组成的装备可修部件闭环保障系统,推导了备件库存水平状态的稳态概率分布,计算了可用度等几个保障绩效度量指标,建立了基于可用度约束的保障系统运作优化模型,并通过仿真分析探讨了保障系统运营管理策略问题。     

装备空投的一般数学模型及模拟计算

装备投放是一种部队快速生成战斗力的机动方法.投放过程涉及到气动力学、气固耦合、装备属性等领域知识.通过合理简化,对投放过程的四个阶段分别进行受力分析,在二维情况下建立了对应的微分方程组模型,并给出了相关算例.考虑实际风速、风向等随机参数的影响,在三维情况下建立了带参的微分方程模型,并随机模拟了装备降落点的范围.建立的数学模型对定点降落,及时把握空投最佳时机有积极的指导意义.     

多元Lanchester方程在装备战损量预计中的应用

在战时装备保障中,装备战损量预计是一难点问题.本文从分析影响装备战损的因素出发,采用多元Lanchester方程寻求解决方案.提出了基于指数多元Lanchester方程的装备战损量预计模型和模型中毁伤系数的确定方法.据此,建立了一种新的装备战损量预计方法,并举例验证.该方法较好的满足了未来信息化条件下作战装备保障的需要,具有重要的参考价值.     

蚁群算法在战损装备抢修任务指派中的应用研究

结合战时装备保障实际情况和战损装备抢修任务特点,分析了现有战损装备抢修任务指派模型的特点及不足.依据紧急程度对战损装备抢修任务进行分类,建立了不同紧急度对应的装备抢修任务指派模型,重点是利用蚁群算法对模型进行求解.最后通过某装备保障想定的实例进行了验证,结果表明该算法操作简单、切实有效,能有效实施战损装备应急抢修任务的指派,在装备保障智能决策系统中有较好的应用前景.     

Approximate analysis of unreliable transfer lines with splits in the flow of material

This paper presents a Markov process model and an approximate decomposition technique for a discrete material transfer line with limited buffer capacity. A fraction of the parts processed at some stations in the line may be scrapped or reworked at dedicated machines to meet product quality requirements. Reworked parts are not sent back into the main line. This leads to splits in the flow of material. Processing times are deterministic and identical for all machines and are taken as the time unit. Machine specific times to failure and to repair are geometrically distributed. The model is analyzed through a decomposition into twomachine systems. We develop new decomposition equations for machines performing split operations. Production rates and inventory levels are computed and compared to simulation results. The results indicate that the method produces useful results for a variety of systems.     

A theoretical model of honeycomb material arresting system for aircrafts

Takeoff and landing overruns account for most of the accidents that occur on or in the immediate vicinity of the runway, and it would cause accidental aircraft damage and loss of life. The current Engineered Material Arresting System (EMAS) materials are weak in water resistance and durability, expensive in acquiring and installing, and have negative environmental impacts. So it is significantly required to find a new alternative material with good mechanical properties, higher arresting coefficient and excellent environmental performance. In this article, the arresting properties of metal honeycomb material are studied. A Tire-Honeycomb material Interaction Mechanical Model (THIMM) is proposed. Combining with the dynamic model of aircraft, the theoretical model is coded by MATLAB to finish arresting simulation on aircraft B737-900ER and B727-100. In addition, finite element model of the tire-honeycomb material interaction was built to verify the correctness of the theoretical model. The results obtained by finite element simulation are in a good agreement with the theoretical results. In comparison with the results for traditional materials, the calculated results show that the honeycomb material can stop the overrunning aircraft more efficiently in the condition that the forces induced by the stopping process are safe for the passengers and aircraft.     

Simulation model of multi-compartment distribution in the catering supply chain

An efficient distribution system of high performance is needed to anticipate market developments in the catering supply chain (CSC) in the Netherlands. A simulation model was developed to analyse a multi-compartment distribution system which should satisfy customer demands for shorter lead times, increased delivery frequency and improved quality of process and product. The simulation model quantifies logistic and financial performances in various alternative logistic scenarios for multi-compartment distribution in the catering supply chain. This stochastic simulation model was constructed on the basis of a value chain analysis yielding activities and performance indicators (PIs). The model proved to be accurate in its predictions when applied to a case situation taken from the Dutch CSC. It is concluded that discrete event simulation is an effective tool to evaluate promising logistic scenarios. The new, multi-compartment method of distribution allowed for a 14% decrease in total costs in the Dutch CSC while satisfying customer demands.     

A hybrid analysis approach for finite-capacity queues with general inputs and phase type service

A new analysis method for queueing systems with general input stream and phase type service time distributions is introduced. The approach combines discrete event simulation and numerical analysis of continuous time Markov chains. Simulation is used to represent the arrival process, whereas the service process is analyzed with numerical techniques. In this way the state of the system is characterized by a probability vector rather than by a single state. The use of a distribution vector reduces the variance of result estimators such that the width of confidence intervals is often reduced compared to discrete event simulation. This, in particular, holds for measures based on rare events or states with a small probability. The analysis approach can be applied for a wide variety of result measures including stationary, transient and accumulated measures. This revised version was published online in June 2006 with corrections to the Cover Date.     

Analysis of IEEE 802.11 non-saturated DCF by matrix analytic methods

In the IEEE 802.11 MAC layer protocol, the basic access method is the Distributed Coordination Function based on the CSMA/CA. In this paper, we investigate the analytic performance of IEEE 802.11 DCF in the non-saturation mode. We assume that there is a fixed number n of competing stations and the packet arrival process to each station is a Poisson process. We model IEEE 802.11 DCF in non-saturation mode by a 3-dimensional Markov chain and derive the steady state probability of the Markov chain by applying the matrix analytic method. We obtain the probability generating function of Head-of-Line delay (HoL-delay), non-saturation throughput and packet loss probability. Our results can be used for finding the optimal number of stations that can be accommodated while satisfying a given QoS requirement. This research is supported by the MIC (Ministry of Information and Communication), Korea, under the ITRC (Information Technology Research Center) support program supervised by the IITA (Institute of Information Technology Assessment).     

Hospital preparedness during epidemics using simulation: the case of COVID-19

Central European Journal of Operations Research - This paper presents a discrete event simulation model to support decision-making for the short-term planning of hospital resource needs, especially...     

Using soft OR principles for collaborative simulation: a case study in the Dutch airline industry

Collaborative simulation is a method to handle problem situations that are technologically and socially complex. It combines discrete event simulation with methods, techniques and tools designed to help groups progress with their problems. Discrete event simulation and group support both appear to have clear promises in embedding soft OR principles, yet also contain limitations. Furthermore, simulation and group support appear to be complementary, balancing each other's limitations. Therefore, the combination of group support and discrete event simulation seems to be a fruitful vehicle for the application of soft OR principles. Through experiences in a case study at the cargo department of a major airline, we examine how collaborative simulation can be applied in practice as problem structuring method. We conclude that collaborative simulation has definite potential as a soft OR technique, but further research is required to speed up different steps of simulation to fully use simulation in interactive decision making sessions with multiple stakeholders.     

Using simulation modelling to support decisions in hail suppression programmes with airborne means

This article presents the development and implementation of a stochastic discrete event simulation model. The project aims to analyse and improve the operational processes of a Hail Suppression Programme with airborne means. The main objective of the programme is the minimization of crop damages because of hailstorms. The project involves a simulation model as part of the decision support analysis, which investigates costs and effectiveness of various operational scenarios concerning the interception and neutralization of hailstorms, using airborne seeding. Apart from estimating responses and metrics under miscellaneous scenarios, the model facilitates what-if analysis to inspect and reveal relations between service (interception) times, number of aircrafts, and acceptable values of efficiency metrics. Subsequently, the model has been used to estimate a regression function that has been further implemented in the assessment process for new technologies and materials.     

Mesoscopic supply chain simulation

This paper reviews and compares existing approaches for supply chain modeling and simulation and applies the mesoscopic modeling and simulation approach using the simulation software MesoSim, an own development. A simplified real-world supply chain example is modeled with discrete event, mesoscopic and system dynamics simulation. The objective of the study is to compare the process of model creation and its validity using each approach. The study examines advantages of the mesoscopic approach for the simulation. Major benefits of the mesoscopic approach are that modeling efforts are balanced with the necessary level of detail and facilitate quick and simple model creation and simulation.