Microstructural evolution and dynamic recrystallization mechanisms of additively manufactured TiAl alloy with heterogeneous microstructure during hot compression

Microstructural evolution and dynamic recrystallization(DRX)mechanisms of a Ti-48Al-2Cr-2Nb(at.%)alloy prepared by selective electron beam melting(SEBM)during hot deformation at 1150℃and 0.1 s^(-1)were investigated by hot compression tests,optical microscope(OM),scanning electron microscope(SEM),electron back-scattered diffraction(EBSD)and transmission electron microscope(TEM).The results show that the initial microstructure of the as-SEBMed alloy exhibits layers of coarseγgrains and fineγ+α_(2)+(α_(2)/γ)lamellar mixture grains alternately along the building direction.During the early stage of hot deformation,deformation twins tend to form within the coarse grains,facilitating subsequent deformation,and a small number of DRX grains appear in the fine-grained regions.With the increase of strain,extensive DRX grains are formed through different DRX mechanisms in both coarse and fine-grained regions,involving discontinuous dynamic recrystallization mechanism(DDRX)in the fine-grained regions and a coexistence of DDRX and continuous dynamic recrystallization(CDRX)in the coarsegrained regions.

基于DS证据理论的极地邮轮减摇鳍选型评价

极地邮轮工作环境特殊,减摇鳍装置的选型需考虑抗低温、抗恶劣海况等在内的诸多因素,单凭主观判断很难选出最优的减摇鳍装置。为解决该问题,提出基于层次分析法(AHP)-熵权法(EWM)、三角模糊理论以及Dempster-Shafer(DS)证据融合的综合评价方法。首先构建环境适应性、装置性能等4个一级指标以及13个二级指标的选型评价指标模型,采用组合赋权法计算定性、定量指标权重;其次构建识别框架及模糊评语集,并邀请专家组对指标做出模糊评价,利用证据距离对DS证据合成策略做出改进,将修正后证据进行两两合成从而得到各方案二级指标mass函数。最后对选型方案进行综合评价,选出符合实际需求的最优减摇鳍装置。结果表明,该方法能充分考虑决策过程的不确定性,对极地邮轮减摇鳍装置选型起到科学决策的作用。

基于拉普拉斯小波滤波和SA-DS-CNN的滚动轴承故障诊断

针对基于深度学习模型的滚动轴承故障诊断方法易受环境噪声干扰的问题,提出了一种基于拉普拉斯小波滤波(LWF)和自注意力机制-动态选择-卷积神经网络(SA-DS-CNN)的滚动轴承故障诊断模型。首先,提出一种拉普拉斯小波阻尼参数自适应选取策略,使用拉普拉斯小波对采集的滚动轴承振动信号进行相关滤波并进行功率谱变换;其次,基于卷积神经网络框架,引入自注意力机制和动态选择机制,构造SA-DS-CNN;最后,利用SA-DS-CNN提取功率谱特征,根据轴承的不同故障状态定位相关特征信息,实现故障特征的提取和诊断。对N205EM圆柱滚子轴承的故障诊断试验表明:LWF降噪效果较好,能为SA-DS-CNN模型提供优秀的训练样本;SA-DS-CNN模型能抑制无用通道信息,增强网络特征学习能力;LWF和SA-DS-CNN组合模型的故障诊断准确率达到99.65%,优于其他组合模型。

A dynamic programming algorithm for network selection in 3G/WLAN

An essential characteristic of the 4th Generation(4G) wireless networks is integrating various heterogeneous wireless access networks.This paper considers the network selection for both admission and handoff strategy problems in heterogeneous network of 3G/WLAN.A novel dynamic programming algorithm is proposed by taking heterogeneous network characteristics,user mobility and different service types into account.The specificity of our approach is that it puts the situations in a new model and makes decisions in stages of different states.Simulation results validate that the proposed scheme can obtain better new call blocking and handoff dropping probability performance than traditional schemes while ensuring quality-of-services(QoS) for both real-time and data connections.

Dynamic Relay Selection Method for Distributed MIMO Relay System

The research on distributed MIMO relay system has been attracting much attention. In this paper, a decode-and-forward scheme distributed MIMO relay system is examined. For upper bound of channel capacity, the distance between transceivers is optimized when the propagation loss is brought close to actuality. Additionally, the number of relay is optimized whether total antenna element is fixed or not. When the number of relay is assumed to be infinite, the dynamic relay selection method based on the transmission rate is proposed. We represent that with the proposed method, the transmit power and the number of relays are saving.

Learning-Based Dynamic Connectivity Maintenance for UAV-Assisted D2D Multicast Communication

Unmanned aerial vehicles(UAVs) enable flexible networking functions in emergency scenarios.However,due to the movement characteristic of ground users(GUs),it is challenging to capture the interactions among GUs.Thus,we propose a learningbased dynamic connectivity maintenance architecture to reduce the delay for the UAV-assisted device-todevice(D2D) multicast communication.In this paper,each UAV transmits information to a selected GU,and then other GUs receive the information in a multi-hop manner.To minimize the total delay while ensuring that all GUs receive the information,we decouple it into three subproblems according to the time division on the topology:For the cluster-head selection,we adopt the Whale Optimization Algorithm(WOA) to imitate the hunting behavior of whales by abstracting the UAVs and cluster-heads into whales and preys,respectively;For the D2D multi-hop link establishment,we make the best of social relationships between GUs,and propose a node mapping algorithm based on the balanced spanning tree(BST) with reconfiguration to minimize the number of hops;For the dynamic connectivity maintenance,Restricted Q-learning(RQL) is utilized to learn the optimal multicast timeslot.Finally,the simulation results show that our proposed algorithms perfor better than other benchmark algorithms in the dynamic scenario.

Dynamic selection scheme for cooperative relay under high mobility environment

The mobility of relay has great influence on the performance of a cooperative relay system.This paper proposes a dynamic selection scheme under the amplify-and-forward communication mode in high mobility environment,based on the estimation of channels and the power allocation for each relay node by comparing it with the pre-set threshold.This scheme is used to choose the cooperative relay dynamically for a multiple relay scenario.Simulation results show that this proposed relay selection scheme decreases the outage probability effectively,maintains system capacity well,and improves the performance of the relay system.

Characteristic Analysis of DS18B20 Temperature Sensor in the High-voltage Transmission Lines’ Dynamic Capacity Increase

Dynamic capacity increase in high voltage electric power transmission line is currently the most economical method for solving electric power transmission bottleneck nowadays. DS18B20 temperature sensor is applied to the dynamic capacity increase of high voltage transmission lines to measure the conductor temperature and ambient temperature. The paper is focused on the experiment of DS18B20 both in the laboratory and outside. From the result of the lab temperature measurement data analysis, using 4 DS18B20’s is the most suitable plan, considering both accuracy and economical efficiency. In the experiment outside, we get four groups of conductor (uncharged) temperature and four groups of ambient temperature. The data proved that DS18B20 has good stability, and small measurement error. It is suitable for measuring the temperature of conductor and ambient in dynamic capacity increase, and helpful to improve the accuracy of the calculation of capacity increasing.

Tensile stress enhanced dynamic oxygen vacancies on interlayer stretched Bi_(2)O_(2)CO_(3) as pivotal knobs to promote sustainable selective CO_(2) photoreduction

Surface oxygen vacancies(OVs) with abundant localized electrons on bismuth-oxygen based photocatalysts are proved to have the ability to capture and activate CO_(2).However,the surface OVs are easily filled with oxygen-containing species and destroyed,losing their effects as active sites and hindering the subsequent CO_(2)photoreduction.For realistic and sustainable CO_(2)photoreduction,constructing sustainable and stable surface OVs as active sites on photocatalysts is essential.This work shows the synthesis of interlayer stretched Bi_(2)O_(2)CO_(3) ultrathin nanosheets with tensile stress,which are beneficial to continuously generating light-induced dynamic OVs.With sufficient active sites,excellent,stable,and selective photoreduction of CO_(2)to CO under simulated solar light is achieved.The light-induced OVs can reduce the energy barrier of rate-determining step,resulting in the 100% product selectivity.The results presented herein demonstrate the effect of dynamic OVs induced by interlayer tensile strain on catalysts for the enhanced selective CO_(2)photoreduction process.

基于生产数据的混合流水车间动态调度方法研究

在智能制造背景下,物联网等信息技术为制造系统积累了大量数据,同时人工智能等先进方法为车间数据分析和实时控制提供了有效手段。因此,针对不相关并行机混合流水车间调度问题,提出了一种基于生产数据的动态调度方法,以实现订单完工时间最小化。首先以高质量调度方案为基础,从中提取生产特征和调度规则完成样本构建。其次使用Relief F算法过滤冗余生产特征,获得用于训练和预测的调度样本。然后采用融合鲸鱼优化算法的概率神经网络作为调度模型,实现基于调度样本的训练和预测过程。最后,实验结果表明,所提方法具有良好的特征选择能力和较高的预测精度,与其他实时调度方法相比具有更加优越的性能,可以有效地根据车间实时状态指导制造执行过程。

A Multi-Hop Dynamic Path-Selection (MHDP) Algorithm for the Augmented Lifetime of Wireless Sensor Networks

In Wireless Sensor Networks (WSN), the lifetime of sensors is the crucial issue. Numerous schemes are proposed to augment the life time of sensors based on the wide range of parameters. In majority of the cases, the center of attraction will be the nodes’ lifetime enhancement and routing. In the scenario of cluster based WSN, multi-hop mode of communication reduces the communication cast by increasing average delay and also increases the routing overhead. In this proposed scheme, two ideas are introduced to overcome the delay and routing overhead. To achieve the higher degree in the lifetime of the nodes, the residual energy (remaining energy) of the nodes for multi-hop node choice is taken into consideration first. Then the modification in the routing protocol is evolved (Multi-Hop Dynamic Path-Selection Algorithm—MHDP). A dynamic path updating is initiated in frequent interval based on nodes residual energy to avoid the data loss due to path extrication and also to avoid the early dying of nodes due to elevation of data forwarding. The proposed method improves network’s lifetime significantly. The diminution in the average delay and increment in the lifetime of network are also accomplished. The MHDP offers 50% delay lesser than clustering. The average residual energy is 20% higher than clustering and 10% higher than multi-hop clustering. The proposed method improves network lifetime by 40% than clustering and 30% than multi-hop clustering which is considerably much better than the preceding methods.

近代物理实验教学流程的模式探索

以中南大学近代物理实验课程实践为例,针对课程特点探索了一种相对稳定又可动态调整的实验教学模式.从立德树人的根本任务出发,将课程思政融入近代物理实验教学;落实“学生为主体”的教学理念,结合学生需求开设实验教学项目,学生以学习组、研究组的形式自主选择实验项目,激发学生的学习兴趣和主体意识;落实“教师为主导”的理念,对课堂环节的具体教学方法保持开放的态度,寻求不同实验教学内容在共性与个性上的统一.同时,在实验教学中对接教师科研成果和物理实验竞赛,培养学生的物理思维和科研素养,达到全面提升实验教学效果的目的.

具有潜在表示和动态图约束的多标签特征选择

针对现有嵌入式方法忽略实例相关性的潜在表示对伪标记学习的影响以及固定的图矩阵导致计算误差随迭代的加深而不断增大的问题,提出一种具有潜在表示和动态图约束的多标签特征选择方法.该方法首先利用实例相关性的潜在表示构造伪标签矩阵,并将其与线性映射和最小化伪标签与真实标签之间的Friedman范数距离相结合,从而保证伪标签与真实标签之间具有较高的相似性.其次,利用伪标签的低维流形结构构建动态图,以缓解固定图矩阵导致的随迭代深度增加计算误差的问题.在12个数据集上与7种先进方法的对比实验结果表明,该方法的整体分类性能优于现有先进方法,能较好地处理多标记特征选择问题.

基于动态模态分解-自适应变步长油浸式电力变压器绕组瞬态温升快速计算方法

为了改善当前油浸式电力变压器绕组瞬态温升计算过慢的问题,该文结合动态模态分解法和自适应变步长法提出了一种动态模态分解(DMD)-自适应变步长(ATS)快速计算方法。首先,该方法引入了动态模态分解算法,利用动态系统中前若干时步提取得到的变化特征,近似拟合其后一段时间内的系统变化,并通过选取主模态降低计算时间。其次,为了提高DMD算法性能,进一步提出结合ATS方法,通过自适应调整计算步长,提高瞬态计算效率;为了验证算法的计算精度和效率,建立了八分区分匝绕组数值传热模型并在此基础上将该文所提算法与仿真软件Fluent的计算结果进行对比,结果表明,在计算精度方面,二者结果几乎一致,计算误差最大不超过0.3 K;对于计算效率,该文算法的总计算时间为5.99 s,仅为Fluent总计算时间的1/89,且算法时间步数仅为Fluent的4.7%。最后,为了验证DMD-ATS算法的工程实用性,基于产品级油浸式电力变压器绕组结构搭建温升实验平台,并将所提算法计算结果与实验结果进行对比,结果表明所提算法在各测量线饼的误差均处在可接受的范围内,最大误差仅为4.57 K,且包含预处理时间在内的计算时间仅为69.14 s,计算时步仅需17步,较当前主流的计算方法效率有明显提高。综合算法的精度和效率,充分说明所提算法具有一定工程价值。

采用动态相关度权重的特征选择算法

基于互信息的特征选择算法在考虑候选特征提供的新分类信息时,通常忽略了候选特征的加入会使得已选特征和类标签的相关性发生变化而带来额外的新增信息量,以及在计算冗余信息时采用累加求和的形式可能导致低估候选特征的冗余程度。针对以上问题,提出动态相关度权重的定义,以更全面地考虑候选特征带来的新信息量成分;提出改进冗余项的定义,采用取最大值和归一化策略,以解决传统算法存在的低估冗余问题;在此基础上提出一种采用动态相关度权重的特征选择算法(feature selection using dynamic relevance weight,FSDRW)。选取五种当前主流的基于互信息的过滤式特征选择算法进行对比实验,在来自加州大学尔湾分校UCI和亚利桑那州立大学ASU的机器学习测试数据集上的实验表明,所提出的算法在分类准确率及综合性能方面具有较好的表现。最后将所提出算法应用于广西某水库工程的微震、爆破信号识别中,算法选取出的特征用于微震信号识别可达到98.86%的分类准确率,验证了算法在实际应用中的有效性。

基于生物入侵的特征选择算法

在自然界中,生物入侵以其发展的迅速和巨大的生态影响而受到关注,所引入种群对合适栖息地的寻找过程往往有其内在的逻辑,种群之间的交流和种群的扩张也在这个过程中起到了重要作用。通过探究种群对适宜栖息地的寻找原理,提出一种基于生物入侵的特征选择(BIAFS)算法。在BIAFS算法中,生物入侵过程分为种群建立、种群迁移、种群交流和扩张、种群发展4个阶段。在实验验证过程中,在9个数据集上将BIAFS算法与8种高性能算法进行实验比较。实验结果显示,BIAFS算法在7个数据集上的分类准确率(CA)和降维(DR)率均超过了对比算法。此外,适应度标准偏差的比较实验也证实了BIAFS算法的高稳定性,表明其在多个数据集上能更加稳健地寻找最优解。上述实验结果证明了BIAFS算法在特征选择任务中的有效性和优越性。

基于组合代价函数的智能汽车轨迹规划

针对智能汽车在多车道公路场景行驶中的安全性、舒适性问题,提出一种基于组合代价函数的轨迹规划方法。利用Frenet坐标系分别求解车辆的横向和纵向运动轨迹,通过五次多项式拟合生成候选轨迹集;以危险程度和轨迹偏离程度为基准,以车辆在多车道公路行驶中的安全性、舒适性为目标,设计一种新的代价函数组合,通过求解代价函数从而选择最优轨迹。仿真结果表明:该方法能够使车辆在三车道动态公路场景中实现跟车与变道。

基于AHP-GIS的建筑垃圾逆向物流产业园选址研究

各类新旧建筑在建造和拆除过程中会产生大量建筑垃圾,从而给建筑垃圾的管理带来巨大压力。为了有效管理建筑垃圾和实现建筑垃圾逆向物流的系统化、规模化、高效化,运用系统动力学理论与方法,构建了建筑垃圾逆向物流SD模型,并对建筑垃圾逆向物流综合效益进行了分析。结合产业园选址要求,从经济、环境、社会3个维度,选取10个影响因素,构建了建筑垃圾逆向物流产业园综合效益选址指标体系。通过AHP确定指标权重,并运用ArcGIS软件对指标图层进行叠加,从而实现建筑垃圾逆向物流产业园的选址。以西安市为例,利用ArcGIS软件中欧氏距离分析、重分类分析和栅格计算器等功能模块分析了各指标的适宜性,得到了西安市建筑垃圾逆向物流产业园的最佳选址区域,验证了模型的可行性。该选址方法可为国内其他城市的相关规划提供参考。

Cooling rate dependence of polymorph selection during rapid solidification of liquid metal zinc

The polymorph selection during rapid solidification of zinc melt was investigated by molecular dynamics simulation. Several methods including g（r）, energy, CNS, basic cluster and visualization were used to analyze the results. The results reveal that the cooling rate has no observable effect on the microstructure as TTc（Tc is the onset temperature of crystallization）; and at the first stage of crystallization, although microstructures are different, the morphologies of nucleus are similar, which are composed of HCP and FCC layers; the polymorph selection of cooling rate finally takes place at the second stage of crystallization： at a high cooling rate, the rapid increase of FCC atoms leads to a FCC crystal mixed with less HCP structures; while at a low cooling rate, HCP atoms grow at the expense of FCC atoms, resulting in an almost perfect HCP phase. The results reveal that the cooling rate is one of the important factors for polymorph selection.

Influence of site selection on natural ventilation in Chinese traditional folk house

The relationship between the site selection of a hilly terrain and the natural ventilation of the Dangdamen building complex,which is a traditional folk house,is revealed by a computational fluid dynamics（CFD）simulation.The wind press and speed distributions around the building in four cases with different weather conditions and topographies are simulated.The simulation results show that a hill can reduce the absolute values of the wind pressure at the windward and leeward sides of the building.The encouraging effect of the patio on the natural ventilation in a terrain with a hill is greater than that without a hill.The same situation occurs when comparing the patio effects between summer and winter.The wind speed around the building can be reduced by the hill as it is an obstacle and the degrees of the influence of the hill in summer and in winter are quite different because of different wind directions.The analysis results show that this kind of site selection,with the hill to the north,is a suitable way to settle the conflict of the natural ventilation requirements in summer and in winter under subtropical climate conditions,especially in houses with patios.