列车编组对桥梁振动响应影响的试验研究

通过对两座桥梁振动测试结果的分析，发现列车编组对桥梁振动响应很有影响，且这一现象过去常常被忽略。本文详细研究了列车编组与桥梁横向振动响应之间的关系，同时还就一座桥梁加固后的试验结果进行分析，指出用改善列车编组的方法提高桥梁动态性能的必要性和可行性。     

胶原对生物组织的增强作用

胶原纤维对生物组织起一种拉伸增强作用．它们的功能可用三种组织的性质来说明：腱、关节软骨和椎间盘．腱在人体的关节周围将肌肉与骨连接在一起．关节软骨覆盖在大部分关节骨的端部表面，椎间盘则连接着脊椎骨使得它成为一种柔性结构．增强度β由组织中胶原的体积分量所定义和确定．增强效应系数η，则依赖于纤维的取向．在键中纤维是波形的．腱的变形的第一步主要是拉直波形纤维以增加η值．其结果是，当应变在低应变值时，应力会迅速增加．当波形纤维被拉直时，η＝１．关节软骨足以支持着外加的压缩是因为它本身具有高的内部膨胀压力．胶原纤维能增强组织则是因为它们的取向使得它们的应变适于这种压力．椎间盘大致是柱状的，它们由内核区和包围内核的环状结构组成．这些环状结构由胶原层组成，每一层内的胶原纤维是平行的，但都与脊椎轴倾斜成一定角度．扭转和弯曲牵伸一些纤维，这种纤维增强了椎间盘．由于不是所有的纤维被牵伸，故所施的压力并不是均匀分布的．于是，扭转和弯曲是潜在的损伤力．椎间盘的压缩使所有的纤维受力．外部压缩会损伤脊椎的骨头而无损于环状结构．     

几种采用熔体注射成型实现聚合物自增强的方法

对当前常用的几种注射自增强方法进行了归纳和总结介绍了高压注射法、拉伸流动法和剪切控制法等几种实现单向自增强的方法以及注射压制二步法、摆动注射法、旋转注射法和剪切控制法等实现双向自增强的方法。     

Innovative processing using ultrafine particulation

Anodic sites like grain-boundaries, micro-voids, micro-inclusions and other stress concentration points such as dislocations, vacancies, etc., take an active part in the galvanic interactions occurring on the surface of metals and alloys. This paper discusses the role of low concentration reinforcement of metals like Zn, Pb and Sn, alloy matrices like Cu-Zn, Cu-Mn, Zn-Al and Al-Zn and non-metals like polyaniline, along with the amorphous Ni-P-B class of current-assisted electroless deposits. It is assumed that ultrafine ceramic particulates in low concentration ranges (1–1.5 wt%) may cover the anodic defect sites such that these anodic boundaries start behaving cathodically as a network, within the already existing cathodic grain matrices, because they are predominantly more cathodic, compared to the grain boundaries, voids, etc. As such, there is a considerable reduction of surface dissolution and in the anodic current of the matrix. It has been shown that surface dissolution is a minimum for a critical threshold concentration of the particulates, above which there is drastic dissolution of the surface. It appears that particulates above that critical concentration cannot be accommodated within the available anodic sites, such that they are dispersed on the grain proper in a random fashion, creating stress spikes and subsequent enhanced matrix dissolution. It further appears that it will thus be possible either to decrease or increase the dissolution of the composite matrices for selective tailor-made applications, by changing the concentration of these ultrafine particulates around the threshold concentration. It has been shown that such a technique may eventually reduce the leaching of copper from conventional brass matrices and also reduce the dissolution of tin in the packaging industries. Grain boundary structures of the metallic matrices have also been correlated with the particulate trapping capacity and their corresponding galvanic stress factors. It has also been applied to amorphous Ni-P-B types of metal-metalloid coatings, for enhancement of surface corrosion resistance. Particulation of epoxy and epoxy-silicone classes of barrier with ultrafine SiC has revealed a more positive potential and lower galvanic currents. Reinforcement of the permalloy type Ni-Fe-Mo class barrier with fine Al₂O₃ particulates has indicated considerable improvement of the polarization resistance values. Received: 25 January 1999 / Accepted: 19 October 1999     

Stability of Conical Shells of Metal Composites Beyond the Elastic Limit

The equations for integral instantaneous characteristics of composite materials consisting of elastoplastic fibers and matrix are derived based on the known hypotheses of uniform strain or stress fields. The constitutive relations for a layered shell are obtained. The numerical algorithm elaborated is used to solve the stability problem for conical boron-aluminum shells under external pressure and axial compression. It is shown that the shells of medium thickness lose their stability under loads whose magnitude depends on the plasticity of the binder. The plasticity has a decisive influence on the choice of the optimum directions of reinforcement. If the parameters of a shell are such that the buckling occurs beyond the elastic limit, the shell must be reinforced in the direction of precritical stresses. However, this is possible only upon separate action of loads.     

SiCp增强铝基复合材料切削加工中刀—屑摩擦模型及其磨损性能研究

通过分析ＳｉＣ颗粒增强铝基复合材料切削过程中刀具与切屑之间的摩擦特点,经过某些合理简化,提出了以紧密接触为主要特征的摩擦特性方程式,通过与切削试验及计算机仿真结果对比,验证了该公式的合理性;并采用ＳＥＭ等手段分析了ＳｉＣ颗粒及晶须增强铝基复合材料及刀具的磨损机理。结果表明：复合材料的耐磨性能优于铝合金;Ｋ类硬质合金刀具有可用于粗加工和半精加工,并须用较低切削速度和较大进给量;而精加工时须采用聚晶金     

Experience-driven learning-based intelligent hybrid beamforming for massive MIMO mmWave communications

We have studied massive MIMO hybrid beamforming (HBF) for millimeter-wave (mmWave) communications, where the transceivers only have a few radio frequency chain (RFC) numbers compared to the number of antenna elements. We propose a hybrid beamforming design to improve the system’s spectral, hardware, and computational efficiencies, where finding the precoding and combining matrices are formulated as optimization problems with practical constraints. The series of analog phase shifters creates a unit modulus constraint, making this problem non-convex and subsequently incurring unaffordable computational complexity. Advanced deep reinforcement learning techniques effectively handle non-convex problems in many domains; therefore, we have transformed this non-convex hybrid beamforming optimization problem using a reinforcement learning framework. These frameworks are solved using advanced deep reinforcement learning techniques implemented with experience replay schemes to maximize the spectral and learning efficiencies in highly uncertain wireless environments. We developed a twin-delayed deep deterministic (TD3) policy gradient-based hybrid beamforming scheme to overcome Q-learning’s substantial overestimation. We assumed a complete channel state information (CSI) to design our beamformers and then challenged this assumption by proposing a deep reinforcement learning-based channel estimation method. We reduced hybrid beamforming complexity using soft target double deep Q-learning to exploit mmWave channel sparsity. This method allowed us to construct the analog precoder by selecting channel dominant paths. We have demonstrated that the proposed approaches improve the system’s spectral and learning efficiencies compared to prior studies. We have also demonstrated that deep reinforcement learning is a versatile technique that can unleash the power of massive MIMO hybrid beamforming in mmWave systems for next-generation wireless communication.     

Properties of Thermoplastic Starch/Kenaf Composite

This paper reports on the physical and mechanical properties of the thermoplastic sago starch/kenaf fibre (TPSS/KF) composite. The composite was prepared through a compression molding technique at varying fibre contents of 0, 10, 20 and 30 wt.%, whilst the effect of the fibres incorporation was evaluated by physical and mechanical tests, as well as morphological analysis. Reduction of moisture content and denser composite were achieved with a higher fibre content. Meanwhile, the water absorption of the composite was lower than the thermoplastic with an increase in the kenaf fibre loading. Tensile testing improved strength and modulus with the increase of fibres content until an optimum was reached at 30 wt.% of fiber loading. Morphological analysis showed good wetting between the polymer matrix and fibres that provided the tensile improvement.     

Novel highly elastic magnetic materials for dampers and seals: Part I. Preparation and characterization of the elastic materials

The new generation of magnetic elastomers represents a new type of composites, consisting of small (mainly nano and micron‐sized) magnetic particles dispersed in a highly elastic polymeric matrix. The combination of polymers with magnetic materials displays novel and often enhanced properties. Highly elastic magnetic composites are quite new and understanding of the behavior of these materials depending on the composition, external conditions, and the synthesis processes is still missing. Thus, the aim of this work is the study of fundamental principles governing the preparation of these materials as well as their structure and elastic properties. Copyright © 2007 John Wiley & Sons, Ltd.     

Development of nano IrO<Subscript>2</Subscript> composite-reinforced nickel–phosphorous electrodes for hydrogen evolution reaction

Electroless and electroplated nickel electrodes are extensively used for hydrogen evolution reaction (HER). In the present work, TiO₂-supported IrO₂ mixed oxide composite was prepared and used to reinforce Ni–P electroless plates to be used as catalytic electrodes for HER. The electrodes exhibited high electrocatalytic activity when the electrodes were used for HER. All the parameters including particle size of the catalyst, surface roughness, and surface active sites were studied. The particle size of the IrO₂ catalyst in the mixed oxide was found to have high influence on the catalytic activity of the electrodes. Low overpotential as low as 70 mV at a current density of 200 mA cm⁻² was achieved with the mixed oxide-reinforced Ni–P electrodes.