MHD mixed convection of a Cu–water nanofluid flow through a channel with an open trapezoidal cavity and an elliptical obstacle

In the current work, numerical simulations are achieved to study the properties and the characteristics of fluid flow and heat transfer of (Cu–water) nanofluid under the magnetohydrodynamic effects in a horizontal rectangular canal with an open trapezoidal enclosure and an elliptical obstacle. The cavity lower wall is grooved and represents the heat source while the obstacle represents a stationary cold wall. On the other hand, the rest of the walls are considered adiabatic. The governing equations for this investigation are formulated, nondimensionalized, and then solved by Galerkin finite element approach. The numerical findings were examined across a wide range of Richardson number (0.1 ≤ Ri ≤ 10), Reynolds number (1 ≤ Re ≤ 125), Hartmann number (0 ≤ Ha ≤ 100), and volume fraction of nanofluid (0 ≤ φ ≤ 0.05). The current study's findings demonstrate that the flow strength increases inversely as the Reynolds number rises, which pushes the isotherms down to the lower part of the trapezoidal cavity. The Nu_avg rises as the Ri rise, the maximum Nu_avg = 10.345 at Ri = 10, Re = 50, ϕ = 0.05, and Ha = 0; however, it reduces with increasing Hartmann number. Also, it increase by increasing ϕ, at Ri = 10, the Nu_avg increased by 8.44% when the volume fraction of nanofluid increased from (ϕ = 0–0.05).     

Method for calculating horizontal drain induced non-linear and large strain degree of consolidation

Consolidating dredged clay slurries using a combination of vacuum pressure and prefabricated horizontal drains (PHDs) is widely used in practice. This is a large strain problem, but there is no existing large strain theory for PHD induced consolidation. A method with explicit equations has been proposed to consider both mechanical and geometrical non-linearities in analyzing PHD induced consolidation. The method considers stepwise variation of properties using imaginary time concept. An imaginary time is determined by the condition of continuity of degree of consolidation before and after changing the properties. Then the method was applied to analyze a large scale model test of vacuum consolidation with PHD. Two analyses were conducted. One considered both the mechanical and geometrical non-linearity (large strain), and another only considered mechanical non-linearity (small strain). The results of large strain analysis agree with the measured settlement curve and excess pore pressures well. While the small strain analysis under-estimated the rate of consolidation significantly. The results from this study indicate that for analyzing PHD induced consolidation of clay slurries considering the effect of large strain is important, and the proposed method can be a useful design tool.     

A comparison of shear stress estimation methods for a single geobag on a rough bed

There are several methods for estimating bed shear stress in the literature, but comprehensive comparisons among them are limited and under specific conditions. This study compared these methods first on a bare smooth bed, and then for a single geobag on a rough bed in the interest of determining the stability of geobags used in riverbank protection structures. The geobag was filled with cement or sand and tested under different open channel flow conditions. The turbulent kinetic energy method appeared to best represent the local bed shear stress on the geobag when using the newly calibrated proportionality constants. The Reynolds stress method via extrapolation was relatively unaffected by changes to the geobags shape and measurement locations, suggesting this method inadequately represents the local bed shear stress. The Patel method and the universal law of the wall method failed to represent local bed shear stress in the rough bed cases due to instrument limitations and the breakdown of the law of the wall. This study highlights the impact of different methods on the bed shear stress estimation.     

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).     

认知双向中继网络在κ-μ衰落信道下的中断性能分析

针对认知双向中继网络在进行数据传输时面临的复杂无线信道场景问题,采用广义κ-μ分布构建认知双向中继网络中的视距和非视距无线传输信道,推导次网络在κ-μ衰落信道下的统一中断概率,并分析次网络在多种单一和混合衰落信道情况下的中断性能。仿真结果表明,无线信道的衰落程度对次网络的中断概率影响显著,依据衰落信道类型合理设置网络参数将有助于提升次网络中断性能。     

Acquisition and Spread of Antimicrobial Resistance: A tet(X) Case Study

Understanding the mechanisms leading to the rise and dissemination of antimicrobial resistance (AMR) is crucially important for the preservation of power of antimicrobials and controlling infectious diseases. Measures to monitor and detect AMR, however, have been significantly delayed and introduced much later after the beginning of industrial production and consumption of antimicrobials. However, monitoring and detection of AMR is largely focused on bacterial pathogens, thus missing multiple key events which take place before the emergence and spread of AMR among the pathogens. In this regard, careful analysis of AMR development towards recently introduced antimicrobials may serve as a valuable example for the better understanding of mechanisms driving AMR evolution. Here, the example of evolution of tet(X), which confers resistance to the next-generation tetracyclines, is summarised and discussed. Initial mechanisms of resistance to these antimicrobials among pathogens were mostly via chromosomal mutations leading to the overexpression of efflux pumps. High-level resistance was achieved only after the acquisition of flavin-dependent monooxygenase-encoding genes from the environmental microbiota. These genes confer resistance to all tetracyclines, including the next-generation tetracyclines, and thus were termed tet(X). ISCR2 and IS26, as well as a variety of conjugative and mobilizable plasmids of different incompatibility groups, played an essential role in the acquisition of tet(X) genes from natural reservoirs and in further dissemination among bacterial commensals and pathogens. This process, which took place within the last decade, demonstrates how rapidly AMR evolution may progress, taking away some drugs of last resort from our arsenal.     

基于LBT-SA的LoRaWAN信道接入方法研究

标准LoRaWAN协议中定义的纯ALOHA信道接入方法在网络负载较大时会造成大量碰撞，使LoRa网络的可扩展性和可靠性受到极大挑战。为此提出了一种将先听后说与模拟退火相结合（Listen Before Talk combined with Simulated Annealing，LBT-SA）的LoRa信道接入方法。该方法通过在设备发送之前先监听信道，降低信道被同时接入的概率，并以成功传输所需退避时间为初始值，搜索更小的退避时间。仿真结果表明，LBT-SA和基于二元指数退避算法的先听后说（Listen Before Talk，LBT）方法在包成功传输率方面保持了高度的一致，并且LBT-SA在周期传输过程中逐渐减少了不必要的退避时间，从而减少了时延。在多达10 000个终端接入单个网关的场景中，该算法的平均退避时间至少降低了16.38%。     

纵轴式掘进机截割头载荷影响因素的仿真分析

针对现有掘进机截割头载荷特性研究方法采用单一影响因素不能全面反映截割头载荷及其波动变化规律的问题,通过分析截割头瞬时载荷,确定了纵轴式掘进机在水平截割工况下截割头载荷的主要影响因素有截割岩石特性、截割头掏槽深度、截割头吃刀深度、截割头转速和截割臂摆速。针对某纵轴式掘进机水平截割工况,采用Matlab对影响截割头载荷的多种因素进行仿真分析,得到了各向载荷及其波动随各因素的变化规律:截割头载荷随着岩壁普氏系数的增大而增加,其中横向阻力增加尤为明显,横向阻力波动程度高于其他方向载荷,且随着岩壁普氏系数的增大呈减小趋势;随着截割头掏槽深度的增加,截割头各向载荷近似呈线性增加,其中升力增加幅度最大,各向载荷波动则随着截割头掏槽深度的增大而减小;随着吃刀深度的增加,截割头载荷总体呈增大趋势,载荷波动程度则随之减小;在截割头转速一定的情况下,截割头载荷均随着截割臂摆速的增加而增大,在同一摆速下,截割头载荷随着截割头转速的减小而增大,横向阻力波动明显高于升力和推进阻力波动,横向阻力和推进阻力波动按截割头载荷规律变化,升力波动则与之相反。截割头载荷波动变化规律与截割头载荷变化规律不尽一致,有时甚至相互冲突。因此,掘进机作业过程中应合理选择截割头掏槽深度、吃刀深度等操作参数和截割头转速、截割臂摆速等运动参数,使各参数相互匹配,以减小掘进机振动,延长使用寿命。     

Experimental Investigation of Heat Storage and Heat Transfer Rates during Melting of Nano-Enhanced Phase Change Materials (NePCM) in a Differentially-Heated Rectangular Cavity

In this work, an experimental study of melting heat transfer of nano-enhanced phase change materials(NePCM) in a differentially-heated rectangular cavity was performed. Two height-to-width aspect ratios of the cavity, i.e., 0.9 and 1.5, were investigated. The model Ne PCM samples were prepared by dispersing graphene nanoplatelets(GNP) into 1-tetradecanol, having a nominal melting point of 37℃, at loadings up to 3 wt.%. The viscosity was found to have a more than 10-fold increase at the highest loading of GNP. During the melting experiments, the wall superheat at the heating boundary was set to be 10℃ or 30℃. It was shown that with increasing the loading of GNP, both the heat storage and heat transfer rates during melting decelerate to some extent, at all geometrical and thermal configurations. This suggested that the use of NePCM in such cavity may not be able to enhance the heat storage rate due to the dramatic growth in viscosity, which deteriorates significantly natural convective heat transfer during melting to overweigh the enhanced heat conduction by only a decent increase in thermal conductivity. This also suggested that the numerically predicted melting accelerations and heat transfer enhancements, as a result of the increased thermal conductivity, in the literature are likely overestimated because the negative effects due to viscosity growth are underestimated.     

Focusing characteristics of the relativistic electron beam transmitting in ion channel

Based on the beam–plasma system model established in this paper, the trajectory of the electron beam in the ion channel is studied quantitatively through the envelope equation. Under different initial system parameters, the focusing transmission conditions of the beam in the ion channel are discussed. Then, a series of particle-in-cell simulations are performed, which generally versifies the theoretical results and shows some further details of the focusing behavior of the beam. It is found that the deceleration of some electrons around the focusing point or the beam–plasma interaction at the ion channel boundary will result in the generation of the residual electrons,which forms the electron return current that leads to the new instabilities influencing the focusing characteristics of the beam.