Flexible, Transparent and Conductive Metal Mesh Films with Ultra‑High FoM for Stretchable Heating and Electromagnetic Interference Shielding

Despite the growing demand for transparent conductive films in smart and wearable electronics for electromagnetic interference(EMI)shielding,achieving a flexible EMI shielding film,while maintaining a high transmittance remains a significant challenge.Herein,a flexible,transparent,and conductive copper(Cu)metal mesh film for EMI shielding is fabricated by self-forming crackle template method and electroplating technique.The Cu mesh film shows an ultra-low sheet resistance(0.18Ω□^(-1)),high transmittance(85.8%@550 nm),and ultra-high figure of merit(>13,000).It also has satisfactory stretchability and mechanical stability,with a resistance increases of only 1.3%after 1,000 bending cycles.As a stretchable heater(ε>30%),the saturation temperature of the film can reach over 110°C within 60 s at 1.00 V applied voltage.Moreover,the metal mesh film exhibits outstanding average EMI shielding effectiveness of 40.4 dB in the X-band at the thickness of 2.5μm.As a demonstration,it is used as a transparent window for shielding the wireless communication electromagnetic waves.Therefore,the flexible and transparent conductive Cu mesh film proposed in this work provides a promising candidate for the next-generation EMI shielding applications.

Determination method of mesh size for numerical simulation of blast load in near-ground detonation

In order to improve the overall resilience of the urban infrastructures, it is required to conduct blast resistant design for important building structures in the city. For complex terrain in the city, it is recommended to determine the blast load on the structures via numerical simulation. Since the mesh size of the numerical model highly depends on the explosion scenario, there is no generally applicable approach for the mesh size selection. An efficient method to determine the mesh size of the numerical model of near-ground detonation based on explosion scenarios is proposed in this study. The effect of mesh size on the propagation of blast wave under different explosive weights was studied, and the correlations between the mesh size effect and the charge weight or the scaled distance was described. Based on the principle of the finite element method and Hopkinson-Cranz scaling law, a mesh size measurement unit related to the explosive weight was proposed as the criterion for determining the mesh size in the numerical simulation. Finally, the applicability of the method proposed in this paper was verified by comparing the results from numerical simulation and the explosion tests and was verified in AUTODYN.

基于Q-Learning的动态BLE Mesh网络高能效路由算法

针对动态低功耗蓝牙(Bluetooth Low Energy, BLE)Mesh网络规范采用的管理式泛洪路由机制所导致的数据包冗余和高能耗的问题,提出了动态BLE Mesh网络高能效路由算法。通过建立基于Q-Learning的BLE Mesh网络路由模型,将BLE Mesh网络中节点的剩余能量、转发成本、移动因子以及接收信号强度指示(Received Signal Strength Indicator, RSSI)纳入到奖励函数的设计中。同时对BLE Mesh网络中的心跳机制进行改进,使网络中的节点更加高效地获取环境信息。采用基于探索的路由发现机制来更新网络中节点的Q值,使其能更加准确反映节点移动所导致的网络拓扑变化。仿真结果表明,该算法在节点能耗和网络开销上均优于传统的管理式泛洪路由机制。

THE SUPERCLOSENESS OF THE FINITE ELEMENT METHOD FOR A SINGULARLY PERTURBED CONVECTION-DIFFUSION PROBLEM ON A BAKHVALOV-TYPE MESH IN 2D

For singularly perturbed convection-diffusion problems,supercloseness analysis of the finite element method is still open on Bakhvalov-type meshes,especially in the case of 2D.The difficulties arise from the width of the mesh in the layer adjacent to the transition point,resulting in a suboptimal estimate for convergence.Existing analysis techniques cannot handle these difficulties well.To fill this gap,here a novel interpolation is designed delicately for the smooth part of the solution,bringing about the optimal supercloseness result of almost order 2 under an energy norm for the finite element method.Our theoretical result is uniform in the singular perturbation parameterεand is supported by the numerical experiments.

Distribution,abundance,and realized niches of meroplankton by two different mesh size nets during spring 2017 in the Southern Yellow Sea,China

Meroplankton play a crucial role in both benthic and pelagic ecosystems.Existing quantitative research on estimating the quantities of meroplankton groups is both underrepresented and inaccurate.To investigate and evaluate the influence of varying mesh sizes(505 and 160μm)on the sampling efficiency of meroplankton,we conducted an examination using two commonly used plankton nets during the spring season in the Southern Yellow Sea(SYS).Our study revealed a total of 12 meroplankton groups,with 9 groups identified in the 505-μm mesh nets and 11 groups in the 160-μm mesh nets.The results demonstrated the superior collection efficiency of the 160-μm net compared to the 505-μm net across the majority of meroplankton groups.Furthermore,we focused on exploring the abundance,distribution patterns,and realized niches of meroplankton collected by the two mesh size nets,and observed that the distribution of meroplankton closely resembled the distribution of possible benthic adults in the SYS.Correlation analysis of the six dominant groups collected in the 160-μm mesh nets revealed that seawater temperature and salinity emerged as the key environmental factors driving variations in meroplankton abundance within the SYS.This study also found that a smaller mesh size net does not necessarily capture meroplankton more comprehensively.A comprehensive understanding of the ecological characteristics of meroplankton requires the combination of two types of nets for research.Our research significantly advances our understanding of the quantification,abundance,and distribution of meroplankton,serving as a valuable contribution to the broader landscape of detailed quantitative meroplankton studies.

Mechanical property of cylindrical sandwich shell with gradient core of entangled wire mesh

To explore the wide-frequency damping and vibration-attenuation performances in the application of aerospace components,the cylindrical sandwich shell structure with a gradient core of entangled wire mesh was proposed in this paper.Firstly,the gradient cores of entangled wire mesh in the axial and radial directions were prepared by using an in-house Numerical Control weaving machine,and the metallurgical connection between skin sheets and the gradient core was performed using vacuum brazing.Secondly,to investigate the mechanical properties of cylindrical sandwich shells with axial or radial gradient cores,quasi-static and dynamic mechanical experiments were carried out.The primary evaluations of mechanical properties include secant stiffness,natural frequency,Specific Energy Absorption(SEA),vibration acceleration level,and so on.The results suggest that the vibration-attenuation performance of the sandwich shell is remarkable when the high-density core layer is at the end of the shell or abuts the inner skin.The axial gradient material has almost no influence on the vibration frequencies of the shell,whereas the vibration frequencies increase dramatically when the high-density core layer approaches the skin.Moreover,compared to the conventional sandwich shells,the proposed functional grading cylindrical sandwich shell exhibits more potential in mass reduction,stiffness designing,and energy dissipation.

Mass transfer enhancement and hydrodynamic performance with wire mesh coupling solid particles in bubble column reactor

It is of vital significance to investigate mass transfer enhancements for chemical engineering processes.This work focuses on investigating the coupling influence of embedding wire mesh and adding solid particles on bubble motion and gas-liquid mass transfer process in a bubble column.Particle image velocimetry(PIV)technology was employed to analyze the flow field and bubble motion behavior,and dynamic oxygen absorption technology was used to measure the gas-liquid volumetric mass transfer coefficient(kLa).The effect of embedding wire mesh,adding solid particles,and wire mesh coupling solid particles on the flow characteristic and kLa were analyzed and compared.The results show that the gas-liquid interface area increases by 33%-72%when using the wire mesh coupling solid particles strategy compared to the gas-liquid two-phase flow,which is superior to the other two strengthening methods.Compared with the system without reinforcement,kLa in the bubble column increased by 0.5-1.8 times with wire mesh coupling solid particles method,which is higher than the sum of kLa increases with inserting wire mesh and adding particles,and the coupling reinforcement mechanism for affecting gas-liquid mass transfer process was discussed to provide a new idea for enhancing gas-liquid mass transfer.

Time-Varying Mesh Stiffness Calculation and Dynamic Modeling of Spiral Bevel Gear with Spalling Defects

Time-varying mesh stiffness(TVMS)is a vital internal excitation source for the spiral bevel gear(SBG)transmission system.Spalling defect often causes decrease in gear mesh stiffness and changes the dynamic characteristics of the gear system,which further increases noise and vibration.This paper aims to calculate the TVMS and establish dynamic model of SBG with spalling defect.In this study,a novel analytical model based on slice method is proposed to calculate the TVMS of SBG considering spalling defect.Subsequently,the influence of spalling defect on the TVMS is studied through a numerical simulation,and the proposed analytical model is verified by a finite element model.Besides,an 8-degrees-of-freedom dynamic model is established for SBG transmission system.Incorporating the spalling defect into TVMS,the dynamic responses of spalled SBG are analyzed.The numerical results indicate that spalling defect would cause periodic impact in time domain.Finally,an experiment is designed to verify the proposed dynamic model.The experimental results show that the spalling defect makes the response characterized by periodic impact with the rotating frequency of spalled pinion.

基于强化学习的大规模多模Mesh网络联合路由选择及资源调度算法

为了平衡新型电力系统中大规模多模Mesh网络的传输可靠性和效率,该文在对优化问题进行描述和分析的基础上提出一种基于强化学习的大规模多模Mesh网络联合路由选择及资源调度算法,分为两个阶段。在第1阶段中,根据网络拓扑结构信息和业务需求,利用一种多条最短路径路由算法,输出所有最短路径。在第2阶段中,提出一种基于多臂老虎机(MAB)的资源调度算法,该算法基于得到的最短路径集合构建MAB的摇臂,然后根据业务需求计算回报,最终给出最优的路由选择及资源调度方式用于业务传输。仿真结果表明,所提算法能够满足不同的业务传输需求,实现端到端路径的平均时延和平均传输成功率的高效平衡。

基于蓝牙Mesh技术的校园绿化浇灌系统设计

调研发现,很多高校对校园绿化管理手段有限,虽投入大量人力、物力,但经济效益差,水资源浪费现象比较突出。基于此,设计了一种以传感器+单片机为终端控制单元、利用蓝牙Mesh组网通信的校园绿化浇灌系统。系统具有组网便捷、覆盖面广、控制灵活、网络健壮性强等优点。实验结果表明:系统在不同的环境因素下,能自主判断植物需求,按照既定策略实施浇灌,系统运行正确率平均达91%。将该系统在高校推广使用,能有效降低后勤运营成本,节约水资源,提高校园绿化养护效率。

蓝牙Mesh网络AODV路由改进算法

蓝牙Mesh网络使用泛洪进行多跳通信,在没有路由机制的情况下,由于消息的连续广播,原有泛洪机制会导致网络开销增大和通信延迟。本文基于能量有效的AODV改进算法E AODV使用MATLAB进行仿真,根据跳数、节点剩余能量、链路质量来选择最优节点进行数据包的转发。仿真结果表明,E-AODV算法可减小蓝牙Mesh网络中RREQ数据包传输数量,通过与传统泛洪、AODV算法比较,该算法能够有效降低数据包传输时延,降低网络能耗,提高网络性能。

软件定义无线Mesh网络多目标路由优化算法

无线Mesh网络(Wireless Mesh network, WMN)中,链路拥塞会导致较长的传输时延和排队时间,因此将链路负载均衡与服务质量结合起来一直是研究热点.本文针对多目标路由优化管理的关键问题,将路由问题表述为整数线性规划(Integer linear programming, ILP)模型,并将无线Mesh网络与软件定义网络(Software defined network, SDN)结合,设计了适应于SD-WMN架构的多目标函数、约束条件以及整体的网络优化模型,此外,由于该整数线性规划模型是NP完全的,本文将改进的人工蜂群的启发式优化算法引入到路由优化算法中,以获得源节点和目的节点之间传输流量的理想路径.本文所提出方法在Mininet网络模拟工具中的仿真结果证明了该算法的有效性,与OSPF、SDNR以及遗传蚁群优化(G-ACO)相比,所提出方法在丢包率、往返时间和负载均衡方面均有不错的改善.

面向算力网络的全光网MESH化组网规划研究

全光承载网络是算力网络的根基和底座,面向算力网络的业务发展需求将呈现MESH化组网的趋势。在分析算力网络对光网络需求的基础上,对比了全光网MESH化组网和传统组网的差异,进而研究全光网络MESH化组网规划思路与规划重点,最后提出了全光网MESH化部署相关建议,以期更好地助力算力网络新发展。

基于蓝牙Mesh技术的酒店客房控制系统设计

针对传统的酒店客房控制系统存在功能单一、布线复杂、扩展性差等问题,提出一种采用蓝牙Mesh组网技术的酒店客房控制系统。该系统采用ESP32系列芯片作为主控制器,通过蓝牙Mesh组网实现客房内部设备之间通信消息的接收和转发,实现了酒店灯光、空调的无线控制和室内环境监测功能。各设备的工作状态数据通过MQTT传输技术上传到云平台,并通过微信小程序实现客房内设备的远程控制。测试结果表明,该酒店客控系统通信正常,并实现了预设功能,具有免布线、功能易扩展等优点。

Measured load spectra of the bearing in high-speed train gearbox under different gear meshing conditions

The load spectrum is a crucial factor for assess-ing the fatigue reliability of in-service rolling element bear-ings in transmission systems.For a bearing in a high-speed train gearbox,a measurement technique based on strain detection of bearing outer ring was used to instrument the bearing and determine the time histories of the distributed load in the bearing under different gear meshing conditions.Accordingly,the load spectrum of the total radial load car-ried by the bearing was compiled.The mean value and class interval of the obtained load spectrum were found to vary non-monotonously with the speed and torque of gear mesh-ing,which was considered to be caused by the vibration of the shaft and the bearing cage.As the realistic service load input of bearing life assessment,the measured load spectrum under different gear meshing conditions can be used to pre-dict gearbox bearing life realistically based on the damage-equivalent principle and actual operating conditions.

A Deep Learning Approach to Mesh Segmentation

In the shape analysis community,decomposing a 3D shape intomeaningful parts has become a topic of interest.3D model segmentation is largely used in tasks such as shape deformation,shape partial matching,skeleton extraction,shape correspondence,shape annotation and texture mapping.Numerous approaches have attempted to provide better segmentation solutions;however,the majority of the previous techniques used handcrafted features,which are usually focused on a particular attribute of 3Dobjects and so are difficult to generalize.In this paper,we propose a three-stage approach for using Multi-view recurrent neural network to automatically segment a 3D shape into visually meaningful sub-meshes.The first stage involves normalizing and scaling a 3D model to fit within the unit sphere and rendering the object into different views.Contrasting viewpoints,on the other hand,might not have been associated,and a 3D region could correlate into totally distinct outcomes depending on the viewpoint.To address this,we ran each view through(shared weights)CNN and Bolster block in order to create a probability boundary map.The Bolster block simulates the area relationships between different views,which helps to improve and refine the data.In stage two,the feature maps generated in the previous step are correlated using a Recurrent Neural network to obtain compatible fine detail responses for each view.Finally,a layer that is fully connected is used to return coherent edges,which are then back project to 3D objects to produce the final segmentation.Experiments on the Princeton Segmentation Benchmark dataset show that our proposed method is effective for mesh segmentation tasks.

Rotator cuff repair with an interposition polypropylene mesh:A biomechanical ovine study

BACKGROUND Chronic large to massive rotator cuff tears are difficult to treat and re-tears are common even after surgical repair.We propose using a synthetic polypropylene mesh to increase the tensile strength of rotator cuff repairs.We hypothesize that using a polypropylene mesh to bridge the repair of large rotator cuff tears will increase the ultimate failure load of the repair.AIM To investigate the mechanical properties of rotator cuff tears repaired with a polypropylene interposition graft in an ovine ex-vivo model.METHODS A 20 mm length of infraspinatus tendon was resected from fifteen fresh sheep shoulders to simulate a large tear.We used a polypropylene mesh as an interposition graft between the ends of the tendon for repair.In seven specimens,the mesh was secured to remnant tendon by continuous stitching while mattress stitches were used for eight specimens.Five specimens with an intact tendon were tested.The specimens underwent cyclic loading to determine the ultimate failure load and gap formation.RESULTS The mean gap formation after 3000 cycles was 1.67 mm in the continuous group,and 4.16 mm in the mattress group(P=0.001).The mean ultimate failure load was significantly higher at 549.2 N in the continuous group,426.4 N in the mattress group and 370 N in the intact group(P=0.003).CONCLUSION The use of a polypropylene mesh is biomechanically suitable as an interposition graft for large irreparable rotator cuff tears.

基于Mesh网络的集群式照明管理系统设计

目前的mesh网络中若使用电池供电的传感器,则设备的频繁通信和控制会导致额外的能源消耗。因此,本文基于mesh网络设计了一款集群式照明管理的系统,通过对该系统总框架的设计,将系统所具备的功能分成了数据采集、网络拓扑结构、集群控制等三个模块。通过实验分析,验证出该系统在数据传输效率、控制精准度以及节能效果等方面均具有显著优势。

Securing 3D Point and Mesh Fog Data Using Novel Chaotic Cat Map

With the rapid evolution of Internet technology,fog computing has taken a major role in managing large amounts of data.The major concerns in this domain are security and privacy.Therefore,attaining a reliable level of confidentiality in the fog computing environment is a pivotal task.Among different types of data stored in the fog,the 3D point and mesh fog data are increasingly popular in recent days,due to the growth of 3D modelling and 3D printing technologies.Hence,in this research,we propose a novel scheme for preserving the privacy of 3D point and mesh fog data.Chaotic Cat mapbased data encryption is a recently trending research area due to its unique properties like pseudo-randomness,deterministic nature,sensitivity to initial conditions,ergodicity,etc.To boost encryption efficiency significantly,in this work,we propose a novel Chaotic Cat map.The sequence generated by this map is used to transform the coordinates of the fog data.The improved range of the proposed map is depicted using bifurcation analysis.The quality of the proposed Chaotic Cat map is also analyzed using metrics like Lyapunov exponent and approximate entropy.We also demonstrate the performance of the proposed encryption framework using attacks like brute-force attack and statistical attack.The experimental results clearly depict that the proposed framework produces the best results compared to the previous works in the literature.

基于蓝牙Mesh分布式控制和平均一致性的智慧照明系统

针对维持电力系统平衡向运行储备提出的更高要求,以及大型室内场所中LED照明负荷成为非旋转储备的问题,设计了一种基于蓝牙Mesh分布式控制和平均一致性算法的智慧照明系统。该照明系统采用蓝牙Mesh组网搭建的分布式网络,结合平均一致性算法,以较低的运算量控制大量灯具,在实现功率调整的同时确保用户舒适度趋于一致。实验结果表明:该系统中所有灯具能够在较短时间内完成目标功率容量的调节,同时减小了功率调节对用户舒适度造成的影响,有着网络资源消耗低、稳定性强、易扩展等优势,可以满足实际需求。