不确定箱重下内河集装箱班轮航线配载决策

与集装箱海运相比内河集装箱班轮运输具有其独特性,同时对于内贸箱而言,货主订舱时箱重信息的不确定性导致其航线配载决策变得更加复杂.本文考虑不确定箱重影响,以最小化航线班轮堆栈占用数量为目标,构建内河集装箱班轮航线配载决策的随机规划模型.为实现求解,基于随机规划理论,采用机会约束描述随机约束,将随机规划模型转化为随机机会约束规划模型,并设计混合邻域搜索算法求解.算法由蒙特卡罗随机模拟、神经元网络训练及邻域搜索启发式3个部分组成.算例研究表明,混合邻域搜索算法的鲁棒性较好,可实现配载计划对不确定因素的有效吸收.     

中国城市道路交通安全特点解析

由于中国正处于机动化、城镇化快速交织发展时期,城市道路与公路交通安全的发展特点不同。针对城市道路交通安全特点,基于2007—2016年城市道路交通事故和交通违法数据,兼顾时序规律和空间规律,梳理归纳城市道路交通安全发展的阶段性特征。进而解析城市道路交通安全特点的形成原因,探讨道路安全与道路设施、出行方式、出行行为之间的内在联系。最后,针对城市道路交通事故发生时间、交叉口和非机动车道交通事故回升、电动自行车交通事故骤增、货车夜间交通事故多发、行人交通事故伤亡数居高、老年群体交通安全风险升高等特征,分别提出推进交通安全管理的对策建议。     

Adaptive Multi-Objective Optimization of Bionic Shoulder Joint Based on Particle Swarm Optimization

To get the movement mode and driving mechanism similar to human shoulder joint, a six degrees of freedom (DOF) serial-parallel bionic shoulder joint mechanism driven by pneumatic muscle actuators (PMAs) was designed. However, the structural parameters of the shoulder joint will affect various performances of the mechanism. To obtain the optimal structure parameters, the particle swarm optimization (PSO) was used. Besides, the mathematical expressions of indexes of rotation ranges, maximum bearing torque, discrete dexterity and muscle shrinkage of the bionic shoulder joint were established respectively to represent its many-sided characteristics. And the multi-objective optimization problem was transformed into a single-objective optimization problem by using the weighted-sum method. The normalization method and adaptive-weight method were used to determine each optimization index’s weight coefficient; then the particle swarm optimization was used to optimize the integrated objective function of the bionic shoulder joint and the optimal solution was obtained. Compared with the average optimization generations and the optimal target values of many experiments, using adaptive-weight method to adjust weights of integrated objective function is better than using normalization method, which validates superiority of the adaptive-weight method.     

Structural Optimization of Hatch Cover Based on Bi-directional Evolutionary Structure Optimization and Surrogate Model Method

Weight reduction has attracted much attention among ship designers and ship owners. In the present work, based on an improved bi-directional evolutionary structural optimization (BESO) method and surrogate model method, we propose a hybrid optimization method for the structural design optimization of beam-plate structures, which covers three optimization levels: dimension optimization, topology optimization and section optimization. The objective of the proposed optimization method is to minimize the weight of design object under a group of constraints. The kernel optimization procedure (KOP) uses BESO to obtain the optimal topology from a ground structure. To deal with beam-plate structures, the traditional BESO method is improved by using cubic box as the unit cell instead of solid unit to construct periodic lattice structure. In the first optimization level, a series of ground structures are generated based on different dimensional parameter combinations, the KOP is performed to all the ground structures, the response surface model of optimal objective values and dimension parameters is created, and then the optimal dimension parameters can be obtained. In the second optimization level, the optimal topology is obtained by using the KOP according to the optimal dimension parameters. In the third optimization level, response surface method (RSM) is used to determine the section parameters. The proposed method is applied to a hatch cover structure design. The locations and shapes of all the structural members are determined from an oversized ground structure. The results show that the proposed method leads to a greater weight saving, compared with the original design and genetic algorithm (GA) based optimization results.     

Calculation of strain amplification matrix for strain invariant failure theory based on representative volume element models with periodical boundary condition

Strain invariant failure theory (SIFT) is a micro-mechanics-based failure theory for multi-scale failure analysis of composite materials originally proposed by Gosse and Christensen. In this paper, the approach for obtaining strain amplification matrix which is a key step for the execution of SIFT is improved by adopting representative volume element (RVE) finite element models considering periodical boundary condition, based on which more actual deformation mode is reflected. The deformation modes and strain data at the characteristic points of the centroid cell of multi-cell RVE model are analyzed and taken as a reference. It can be concluded that more reasonable deformation mode and relationship between the micro-mechanical and macro-mechanical strain states are obtained by employing the new model. Finally, numerical examples are provided to illustrate the determination of strain amplification factors within the RVEs considering periodical boundary condition at the characteristic points.     

CT reconstruction with priori MRI images through multi-group datasets expansion

Computed tomography (CT) reconstruction with a well-registered priori magnetic resonance imaging (MRI) image can improve reconstruction results with low-dose CT, because well-registered CT and MRI images have similar structures. However, in clinical settings, the CT image of patients does not always match the priori MRI image because of breathing and movement of patients during CT scanning. To improve the image quality in this case, multi-group datasets expansion is proposed in this paper. In our method, multi-group CT-MRI datasets are formed by expanding CT-MRI datasets. These expanded datasets can also be used by most existing CT-MRI algorithms and improve the reconstructed image quality when the CT image of a patient is not registered with the priori MRI image. In the experiments, we evaluate the performance of the algorithm by using multi-group CT-MRI datasets in several unregistered situations. Experiments show that when the CT and priori MRI images are not registered, the reconstruction results of using multi-group dataset expansion are better than those obtained without using the expansion.     

AZ91基底上多弧离子制备TiN膜及其性能表征

Introduction Magnesium,abundant in natural resource, has many advantages. This make the magnesium alloys attractive as a substitute material of ferrous metals and aluminum alloys. However, there are some unsatisfactory characteristics, which have limited the actual useof magnesium alloys.     

新能源公交车辆大数据决策支持平台的研究

新能源汽车具有能源利用效率高、环境污染小、适用清洁能源种类多、噪声低、方便保养、安全性高等优点,成为未来公共交通发展的重点方向。为了实现更高的信息化程度,为国内大型城市的新能源公交车辆的规模化应用提供便利,相关的信息化系统平台的建设非常重要。大数据技术为新能源公交车辆决策支持平台建立了数据分析与应用基础,该大数据决策支持平台能够存储、处理来自不同数据源的多维数据,利用联机分析处理实现多维度数据分析,运用数据挖掘技术利用新能源公交车辆信息,提供新能源车辆充电决策、充电场地建设决策、电池容量及衰退分析等功能。     

带型城市空间形态界定及其干线道路特征

特殊的空间形态、稀缺的贯通性轴向道路资源以及高度混合的内外交通导致带型城市面临独特的交通问题。从城市空间形态角度出发,采用聚类分析法分析中国657个设市城市,据此界定带型城市为建成区长宽比大于3的城市。并对带型城市(组团)的交通需求、路网布局、道路级配进行梳理,发现带型城市贯穿性长轴干线道路的数量、等级、分布对带型城市规模、形态以及交通组织具有重要作用,是带型城市路网规划的核心。最后,提出带型城市常用的三轴干线路网布局模式及相应的道路等级,可作为带型城市路网规划的参考依据。     

预应力混凝土梁超载能力分析

为了验证利用有限元法分析预应力混凝土梁极限承载能力的准确性,对T形预应力混凝土模型梁进行了极限承载力加载破坏试验,采用ANSYS有限元程序,建立了T梁的分离式有限元模型,分析了模型梁从加载到破坏全过程的受力和变形。发现利用实验与有限元法得到T梁的荷载-挠度曲线与荷载-应变曲线的变化趋势一致,并呈现良好的非线性,但是通过荷载试验得到T梁的超载能力为9.07 kN.m,按照有限元分析得到的超载能力为12.48 kN.m,偏差较大,原因是分析模型偏于理想化。分析结果表明:利用有限元法在总体上能够有效地模拟钢筋混凝土梁受力全过程中各个量的非线性变化,对超载能力的求解是可行的。