Nonlinear Relationship and Its Evolutionary Trace between Node Degree and Average Path Length of China Aviation Network Based on Complex Network

In order to reveal the complex network characteristics and evolution principle of China aviation network,the relationship between the node degree and the average path length of China aviation network in 1988,1994,2001,2008 and 2015 was studied.According to the theory and method of complex network,the network system was constructed with the city where the airport was located as the network node and the airline as the edge of the network.On the basis of the statistical data,the node average path length of China aviation network in 1988,1994,2001,2008 and 2015 was calculated.Through regression analysis,it was found that the node degree had a logarithmic relationship with the average length of node path,and the two parameters of the logarithmic relationship had linear evolutionary trace.Key word:China aviation network,complex network,node degree,average length of node path,logarithmic relationship,evolutionary trace.

Nonlinear Relationship and Its Evolutionary Trace between Average Degree and Average Path Length of Edge Vertices of China Aviation Network Based on Complex Network

In order to reveal the complex network characteristics and evolution principle of China aviation network,the relationship between the average degree and the average path length of edge vertices of China aviation network in 1988,1994,2001,2008 and 2015 was studied.According to the theory and method of complex network,the network system was constructed with the city where the airport was located as the network node and the airline as the edge of the network.On the basis of the statistical data,the average degree and average path length of edge vertices of China aviation network in 1988,1994,2001,2008 and 2015 were calculated.Through regression analysis,it was found that the average degree had a logarithmic relationship with the average path length of edge vertices and the two parameters of the logarithmic relationship had linear evolutionary trace.

Analysis of Channeling-Path Phenomena in a Complex Fault-Block Reservoir with Low Recovery Factor and High Water-Cut Ratio

Current methods for the analysis of channeling-path phenomena in reservoirs cannot account for the influence of time and space on the actual seepage behavior.In the present study,this problem is addressed considering actual production data and dynamic characteristic parameters quantitatively determined in the near wellbore area by fitting the water-cut curve of the well.Starting from the dynamic relationship between injection and production data,the average permeability is determined and used to obtain a real-time quantitative characterization of the seepage behavior of the channeling-path in the far wellbore area.For the considered case study(Jidong oilfield),it is found that the seepage capacity of the channeling-path in the far wellbore area is far less(10 times smaller)than that of the channeling-path in the near wellbore area.The present study and the proposed model(combining near wellbore area and far wellbore area real-time data)have been implemented to support the definition of relevant adjustment measures to ultimately improve oil recovery.

Optimizing Connections:Applied Shortest Path Algorithms for MANETs

This study is trying to address the critical need for efficient routing in Mobile Ad Hoc Networks(MANETs)from dynamic topologies that pose great challenges because of the mobility of nodes.Themain objective was to delve into and refine the application of the Dijkstra’s algorithm in this context,a method conventionally esteemed for its efficiency in static networks.Thus,this paper has carried out a comparative theoretical analysis with the Bellman-Ford algorithm,considering adaptation to the dynamic network conditions that are typical for MANETs.This paper has shown through detailed algorithmic analysis that Dijkstra’s algorithm,when adapted for dynamic updates,yields a very workable solution to the problem of real-time routing in MANETs.The results indicate that with these changes,Dijkstra’s algorithm performs much better computationally and 30%better in routing optimization than Bellman-Ford when working with configurations of sparse networks.The theoretical framework adapted,with the adaptation of the Dijkstra’s algorithm for dynamically changing network topologies,is novel in this work and quite different from any traditional application.The adaptation should offer more efficient routing and less computational overhead,most apt in the limited resource environment of MANETs.Thus,from these findings,one may derive a conclusion that the proposed version of Dijkstra’s algorithm is the best and most feasible choice of the routing protocol for MANETs given all pertinent key performance and resource consumption indicators and further that the proposed method offers a marked improvement over traditional methods.This paper,therefore,operationalizes the theoretical model into practical scenarios and also further research with empirical simulations to understand more about its operational effectiveness.

Path Planning Method Based on D^(*) lite Algorithm for Unmanned Surface Vehicles in Complex Environments

In recent decades,path planning for unmanned surface vehicles(USVs)in complex environments,such as harbours and coastlines,has become an important concern.The existing algorithms for real-time path planning for USVs are either too slow at replanning or unreliable in changing environments with multiple dynamic obstacles.In this study,we developed a novel path planning method based on the D^(*) lite algorithm for real-time path planning of USVs in complex environments.The proposed method has the following advantages:(1)the computational time for replanning is reduced significantly owing to the use of an incremental algorithm and a new method for modelling dynamic obstacles;(2)a constrained artificial potential field method is employed to enhance the safety of the planned paths;and(3)the method is practical in terms of vehicle performance.The performance of the proposed method was evaluated through simulations and compared with those of existing algorithms.The simulation results confirmed the efficiency of the method for real-time path planning of USVs in complex environments.

Design Change Model for Effective Scheduling Change Propagation Paths

Changes in requirements may result in the increasing of product development project cost and lead time, therefore, it is important to understand how require- ment changes propagate in the design of complex product systems and be able to select best options to guide design. Currently, a most approach for design change is lack of take the multi-disciplinary coupling relationships and the number of parameters into account integrally. A new design change model is presented to systematically analyze and search change propagation paths. Firstly, a PDS-Be- havior-Structure-based design change model is established to describe requirement changes causing the design change propagation in behavior and structure domains. Secondly, a multi-disciplinary oriented behavior matrix is utilized to support change propagation analysis of complex product systems, and the interaction relationships of the matrix elements are used to obtain an initial set of change paths. Finally, a rough set-based propagation space reducing tool is developed to assist in narrowing change propagation paths by computing the importance of the design change parameters. The proposed new design change model and its associated tools have been demonstrated by the scheduling change propagation paths of high speed train＇s bogie to show its feasibility and effectiveness. This model is not only supportive to response quickly to diversified market requirements, but also helpful to satisfy customer require- ments and reduce product development lead time. The proposed new design change model can be applied in a wide range of engineering systems design with improved efficiency.

A method of searching fault propagation paths in mechatronic systems based on MPPS model

In view of the structure and action behavior of mechatronic systems,a method of searching fault propagation paths called maximum-probability path search(MPPS)is proposed,aiming to determine all possible failure propagation paths with their lengths if faults occur.First,the physical structure system,function behavior,and complex network theory are integrated to define a system structural-action network(SSAN).Second,based on the concept of SSAN,two properties of nodes and edges,i.e.,the topological property and reliability property,are combined to define the failure propagation property.Third,the proposed MPPS model provides all fault propagation paths and possible failure rates of nodes on these paths.Finally,numerical experiments have been implemented to show the accuracy and advancement compared with the methods of Function Space Iteration(FSI)and the algorithm of Ant Colony Optimization(ACO).

A self-organizing shortest path finding strategy on complex networks

The shortcomings of traditional methods to find the shortest path are revealed, and a strategy of finding the self- organizing shortest path based on thermal flux diffusion on complex networks is presented. In our method, the shortest paths between the source node and the other nodes are found to be self-organized by comparing node temperatures. The computation complexity of the method scales linearly with the number of edges on underlying networks. The effects of the method on several networks, including a regular network proposed by Ravasz and Barabasi which is called the RB network, a real network, a random network proposed by Ravasz and Barabasi which is called the ER network and a scale-free network, are also demonstrated. Analytic and simulation results show that the method has a higher accuracy and lower computational complexity than the conventional methods.

Electron inelastic mean free paths in solids:A theoretical approach

In the present paper, the inelastic mean free path （IMFP） of incident electrons is calculated as a function of energy for silicon （Si）, oxides of silicon （SiO2）, SiO, and A1203 in bulk form by employing atomic/molecular inelastic cross sections derived by using a semi-empirical quantum mechanical method developed earlier. A general agreement of the present results is found with most of the available data. It is of great importance that we have been able to estimate the minimum IMFP, which corresponds to the peak of inelastic interactions of incident electrons in each solid investigated. New results are presented for SiO, for which no comparison is available. The present work is important in view of the lack of experimental data on the IMFP in solids.

A greedy path planning algorithm based on pre-path-planning and real-time-conflict for multiple automated guided vehicles in large-scale outdoor scenarios

With the wide application of automated guided vehicles(AGVs) in large scale outdoor scenarios with complex terrain,the collaborative work of a large number of AGVs becomes the main trend.The effective multi-agent path finding(MAPF) algorithm is urgently needed to ensure the efficiency and realizability of the whole system. The complex terrain of outdoor scenarios is fully considered by using different values of passage cost to quantify different terrain types. The objective of the MAPF problem is to minimize the cost of passage while the Manhattan distance of paths and the time of passage are also evaluated for a comprehensive comparison. The pre-path-planning and real-time-conflict based greedy(PRG) algorithm is proposed as the solution. Simulation is conducted and the proposed PRG algorithm is compared with waiting-stop A^(*) and conflict based search(CBS) algorithms. Results show that the PRG algorithm outperforms the waiting-stop A^(*) algorithm in all three performance indicators,and it is more applicable than the CBS algorithm when a large number of AGVs are working collaboratively with frequent collisions.

Anticlockwise P-T Path and Zircon U-Pb Dating of HP Mafic Granulites in Yushugou Granulite-Peridotite Complex, Southern Tianshan Mountains, China

The Yushugou HP granulite-peridotite complex is located at east of northern margin of southern Tianshan mountains,China,which consists of granulite unit and peridotite unit mainly.Because of the rare association of

清代诗歌的复杂性生成背景与可能性研究进路

清诗是在清代社会历史的土壤上生成的,历史的复杂性决定了诗人情感世界的复杂,诗思书写的复杂。作为一种“复杂关系”中的个体,清代诗人们的创作由身世而及民生,由家国而及社会,由种教而及民族,内容极为丰富,且作品数量庞大。在中国古代诗史的最后一个阶段,往代诗歌发展的每一个知识板块都由川流而成江河,造就出一个规模巨大的诗歌王国。这个诗歌王国至今尚存在很多未知因素,有很多需要探索、垦拓的领域。在现有条件下开展清诗研究,应重视清代诗人天下观、国家观、民族观的变化,于新的文化理念中展开古今通变的思考,并注意对应具体现象和问题,去采取有效方法,寻求可能进路。

机器人磨抛复杂曲面加工轨迹对表面质量的影响研究

为了探究不同加工轨迹及其排布对工件磨抛加工表面质量的影响,本文进行了机器人磨抛轨迹对工件表面质量影响规律的研究。基于Preston去除方程和Hertz接触理论建立了砂带磨抛加工材料去除深度模型,分析了表面残留纹理的生成机理。以曲面航空发动机叶片为试验样件,利用自行搭建的机器人磨抛系统,分别使用等距轨迹、摆线轨迹进行加工试验,分析材料去除效果及表面纹理情况。试验结果表明,采用传统直线加工的等距轨迹于搭接处产生条带状纹理;摆线因其多方向性的加工动作,均化了表面纹理,提高了加工表面一致性。

反射镜式光电系统光路内嵌复合轴稳定误差分析

为满足各类装备平台对反射镜式光电系统光路内嵌复合轴高精度稳定的需求,针对实际研制中各类误差源相互耦合难以控制的难题,文中基于反射镜式光电系统光路内嵌复合轴稳定的原理,从理论上分析了快速反射镜角度与瞄准线角度关系线性化、陀螺和快速反射镜安装正交性误差以及快速反射镜测角精度对系统瞄准线稳定误差的影响,建立了瞄准线稳定误差与上述影响因素之间量化数学模型,并根据量化模型开展了计算仿真实验。仿真结果表明,在瞄准线稳定误差要求为2μrad级别时,快速反射镜角度与瞄准线偏转角度关系不能采用简化的线性化处理,陀螺安装误差应小于0.005 mrad,快速反射镜的安装误差应小于0.003 mrad,快速反射镜的测角精度应达到0.001 mrad。在实际应用中,在保证快速反射镜测角精度的基础上,应对陀螺和快速反射镜安装误差进行校准补偿,确保陀螺和快速反射镜安装误差产生的瞄准线稳定误差绝对值之和小于瞄准线稳定精度要求。

低计算量的窄带ANC算法优化及实车DSP系统试验分析

车内主动噪声控制中常使用的传统滤波-x最小均方(Filtered-x Least Mean Square,FxLMS)算法由于计算复杂度高,往往导致系统硬件算力不足,降噪效果不理想。文章提出一种基于改进局部次级通路建模方法的自适应陷波(Local-secondary-path Filtered-x Least Mean Square,LFxLMS)算法及其相应的窄带主动噪声控制(LFxLMS-based Narrowband Active Noise Control,LFx-NANC)系统。所提出的改进局部次级通路建模方法具有更高的建模精度,且该系统相较于传统系统大大降低了计算复杂度。通过基于Matlab软件的仿真分析,验证了该系统对稳态及非稳态多谐波噪声的降噪性能。基于ADSP-21489控制器搭建车内双通道LFx-NANC系统,实现了在稳态工况下主驾位置处二、四、六阶降噪量分别达到34.67、21.41、10.29 dB(A);在加速工况下主驾位置处总声压级和二阶降噪量分别达到6.01 dB(A)和20.40 dB(A),同时在其他位置均有较好的降噪效果。文中提出的方法为主动噪声控制的工程应用提供了参考。

复杂运动路径下滑坡转向变形机理研究

滑坡受地表地形地貌和滑面形态的影响,在运动过程中常表现出转向、分叉、聚合等复杂行为,研究复杂运动路径下滑坡转向变形机理对滑坡的防灾减灾工作有重要意义。以三维地质建模技术为基础,构建庞家湾滑坡的三维颗粒流模型。通过PFC模拟滑坡的运动过程,得到如下结论:庞家湾滑坡发生了转向和聚合行为,滑坡中后部土体的滑动方向发生偏转并在坡脚与东北区域滑体聚合;滑坡中部发生转向运动的颗粒以较快的速度首先开始滑动,且速度由滑坡中部向周围呈辐射状减小;滑坡前缘在整个运动过程中,始终保持较快的运动速度,而后缘运动速度较慢,此外滑体表面速度大于滑体内部和底面速度,而滑坡各部分运动速度不同则是造成滑坡转向变形的重要原因。揭示了复杂路径滑坡的运动规律和转向变形机理,为评估滑坡风险,采取更为合理的防治方案提供理论依据。

随机矩阵理论在高速路关键路径辨识中的应用

高速公路网络是我国各地区相互连接的重要纽带,高速公路网络关键路径辨识对确保高速网络的可靠运行具有重要意义。传统的关键路径分析方法基于拓扑结构,未考虑交通网络的运输量特性;而现有的基于运输量数据的分析方法只考虑部分路径的运输量特性,难以反映交通网络的实际运行情况。利用路径运输量数据,搭建运输量随机矩阵模型,针对高速公路网络异常后的运输量变化特性,定义关键路径评估指数,实现异常影响程度的量化评估,在此基础上提出一种基于数据驱动的高速公路网络关键路径辨识方法。最后,采用辽宁省高速公路网络进行分析,验证了所提方法的合理性和有效性,并将该方法应用于城市路网案例中,进一步证明该方法具有普适性。

基本路径测试技术及应用研究

基本路径测试法是一种白盒测试方法,文章将程序流程图映射成流图,探讨了程序的3种基本结构映射成流图的方法,计算了流图的环形复杂度并确定了基本测试路径,从而为每条基本路径设计了测试用例。实践证明,基本路径测试法适用于执行路径较多的程序,通过选择有代表性的路径进行测试,可有效提高测试效率。

山区铁路隧道钻爆法施工安全风险演化路径及防控研究

山区铁路隧道钻爆法施工安全风险突出,探索安全风险演化路径并提出安全风险防控措施,对减少安全事故发生意义重大。针对山区铁路隧道钻爆法施工特点,运用文本挖掘分析历史安全事故资料、铁路标准规范资料、现场安全风险评估报告、相关研究文献资料等,结合“4M1E”理论和专家经验识别山区铁路隧道钻爆法施工主要安全风险因素和安全风险事件。采用质性分析法,结合现场调研和专家访谈,提取安全风险因素间、安全风险事件间、安全风险因素及事件间相互关系,构建山区铁路隧道钻爆法施工安全风险演化网络模型。基于风险演化理论、复杂网络理论等,利用度中心性、介数中心性、聚类系数、特征向量中心性、中间中心度等多项指标分析山区铁路隧道钻爆法施工安全风险演化网络节点重要度、边的关键性,从而确定关键链演化路径,并提出安全风险防控措施。研究结果表明:山区铁路隧道钻爆法施工安全风险包括人员、设备、技术、管理、环境5类共41个主要安全风险因素和塌方、突泥涌水等6个主要安全风险事件,确定了安全风险演化网络中8个关键节点、20条关键边和3条关键链,针对关键链风险演化路径提出了安全风险防控措施,为提高山区铁路隧道钻爆法施工安全风险管理水平提供参考。

考虑复杂扰动的轻型商用车路径跟踪混合控制方法

外界扰动、模型不确定性和参数摄动等复杂扰动直接影响智能车辆路径跟踪控制的精度和行驶安全性。商用车的载重特性使其在行驶过程中受到的复杂扰动更为明显,为提升自动驾驶商用车路径跟踪精度和平顺性,提出一种路径跟踪混合控制方法。首先,建立鲁棒性强的基于扩张观测器的滑模控制器和变化平稳的增量式LQR控制器,其中增量式LQR的参数使用粒子群算法整定。然后,使用模糊控制器将两者相结合,根据车速和横向误差调整权重系数,在提升系统鲁棒性的同时削弱抖振。最后,进行了仿真分析和实车试验。试验数据表明,SMC+LQR具备较好的控制效果,能应对外界的复杂扰动。