基于灰色关联分析的飞机客制化模型研究

在飞机设备选型时,客户需要对制造商给出的标准规范清单进行选择,以得到符合其个性化需求的设备,文中对该客制化流程进行了研究.根据灰色关联分析法建立模型,评估待选设备与客户定制需求的关联程度,同时将客户的个性化需求用层次分析法定量化表示成评估指标体系的权重差异.灰色关联度是评估待选设备是否纳入购买清单的依据,反映了待选设备对需求的符合程度.最后以A320-200飞机的客舱可选项为例,应用于2家航空公司不同的个性化需求下,得到了2家公司不同的设备购买优先次序和选项清单.比较结果验证了客制化模型的合理性,从而为飞机设备选型提供了客观的依据.      

适应大型飞机的沥青道面结构有限元模型

借助ABAQUS通用有限元软件,建立了3层道面结构有限元模型,分析了模型的几何尺寸、边界条件、层间接触条件、单元类型、网格的划分对大型飞机荷载作用下道面结构力学响应的影响,提出了适应大型飞机的机场沥青道面结构有限元模型参数,并用实测力学响应数据对模型的有效性进行了验证。研究结果表明:在大型飞机全起落架荷载作用下,有限元模型几何尺寸宜为30m×30m×10m,层间完全连续选用tie连接;单元类型宜采用C3D8R,荷载区域的单元大小控制在不大于0.05m×0.05m;模型底部所有位移全部约束,模型四周约束对应水平方向的位移。实测数据验证结果表明有限元模型有效。     

运动车辆检测的APG-TR算法

为了提高智能交通系统中运动车辆检测的准确率,提出了一种基于张量恢复的APG-TR算法。采用张量表征交通视频图像,保持视频图像高维结构特征。通过张量恢复,重建出张量的低秩部分与稀疏部分,实现交通视频图像中交通背景与运动目标车辆的分离与交通视频内在特征的提取。利用交通监控系统采集到的交通视频106帧图像对本文算法进行了测试。测试结果表明:在晴天条件下,APG-TR算法的平均正确率为91.4%,在雨、雾天气条件下,正确率分别为86.4%、85.2%,相比帧差法更加稳定与准确。APG-TR算法具有良好的收敛速度与鲁棒性,在智能交通领域中具有广泛的应用前景。     

机场水泥混凝土道面飞机荷载影响深度分析

荷载影响深度是研究机场道面沉降的重要参数。本文采用ABAQUS有限元软件为平台,针对4C、4D和4E等级机场分别提出了相应的＂道面结构-飞机荷载＂组合形式,并借鉴公路研究思路,通过对比基础内的荷载应力与自重应力,分别采用σZ/σB=0.1和σZ/σB=0.2两种判断标准,得到了不同土质、不同等级机场条件下的基础影响深度。研究表明,不同土质对基础影响深度的影响非常小;不同等级机场的基础影响深度相差可达100%。     

飞行冲突解脱与恢复几何模型及管制策略

已知两航空器的三维位置、速度及本机预计到达目标点时间,得出了满足几何最优和机动次数最少、解决飞行冲突并同时保证预计到达目标时间不变条件的多种冲突解脱与恢复模型.仿真计算验证了所得模型的有效性.该模型适用于机载设备及空中交通管制自动化系统.在此模型上经大量仿真,综合出了切保护区边界这极限情况并适合空中交通管制员调配的冲突解脱与恢复管制策略表.空中交通管制员只需考虑一定的安全裕量,这些策略即可应用于在实际管制中.     

基于ESS法的重载货车焊缝疲劳仿真

为验证ESS方法的有效性,以装甲钢T型焊接接头为对象,进行了仿真计算与疲劳试验,结果表明,ESS方法计算精度较高,试验与计算误差为18.8%.基于ESS法及静态应力恢复原理,对重载浴盆货车车体关键焊缝进行了疲劳仿真分析,获得了ESS分布规律及仿真结果,其中枕梁上盖板与中梁焊缝计算里程约为2 886万公里,有较高的安全裕度.     

Effective aircraft maintenance schedule adjustment following incidents

In the real world, planned aircraft maintenance schedules are often affected by incidents. Airlines may thus need to adjust their aircraft maintenance schedules following the incidents that occur during routine operations. In tradition, such aircraft maintenance schedule adjustment has been performed manually, a process which is neither effective nor efficient, especially when the problem scale is large. In this study, an aircraft maintenance schedule adjustment model is developed, with the objective of minimizing the total system cost, subject to the related operating constraints. The model is formulated as a zero-one integer program and is solved using a mathematical programing solver. The effectiveness of the model is evaluated by application to a case study using data from an aircraft maintenance center in Taiwan. The test results show the proposed model, as well as the scheduling rules abstracted from the results are useful for the decision maker to adjust good maintenance schedules.     

A three-stage least squares approach to the analysis of airline strategies for aircraft size and airline frequency on the north Atlantic: an airline case study

In response to increasing demand, airlines may increase capacity by increasing the frequency of flights or they may choose to increase aircraft size. This may yield operating cost economies. If the airports they operate from are capacity constrained, they will be limited in the extent that they can change frequency which will limit their ability to compete with the number of frequencies offered. This article focuses on this trade-off and pays particular attention to the practices of a specific airline. Conclusions are offered on the impact of inter alia competition, changes in aircraft technology, 9/11 and the impact of slot constraints. It appears that changes in size are more important than frequency, which is consistent with the presence of slot constraints and there is a significant impact of competition. As the concentration of carriers increases, so aircraft size falls. 9/11 also has a significant impact on traffic whereas the introduction of the Boeing 777, as an illustration of a change in technology, does not.     

Disruption Management of an Inequality-Based Multi-Fleet Airline Schedule by a Multi-Objective Genetic Algorithm

Abstract

This paper presents a novel application of a Method of Inequality-based Multi-objective Genetic Algorithm (MMGA) to generate an efficient time-effective multi-fleet aircraft routing algorithm in response to the schedule disruption of short-haul flights. It attempts to optimize objective functions involving ground turn-around times, flight connections, flight swaps, total flight delay time and a 30-minute maximum delay time of original schedules. The MMGA approach, which combines a traditional Genetic Algorithm (GA) with a multi-objective optimization method, can address multiple objectives at the same time, then explore the optimal solution. The airline schedule disruption management problem is traditionally solved by Operations Research (OR) techniques that always require a precise mathematical model. However, airline operations involve too many factors that must be considered dynamically, making a precise mathematical model difficult to define. Experimental results based on a real airline flight schedule demonstrate that the proposed method, Multi-objective Optimization Airline Disruption Management by GA, can recover the perturbation efficiently within a very short time. Our results further demonstrate that the application can yield high quality solutions quickly and, consequently, has potential to be employed as a real-time decision support tool for practical complex airline operations.     

码头油气回收工艺设计要点

在易挥发的油品及石油产品装船过程中会从油舱内排出油气,工程项目的环境影响报告书已经越来越明确要求要有相应的措施回收这些排出的油气,减少对大气环境的污染,但这些油气回收技术目前并不十分完备。本文以中委合资广东石化2 000万t/a重油加工工程产品码头工程为例,对码头油气回收工艺设计要点进行分析。