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).     

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。     

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%。     

150单缸机试验台冷却系统流动与传热计算分析

基于Flowmaster软件建立了150单缸柴油机试验台冷却系统流动与传热模型,并在某大功率发动机上进行了验证。在此基础上分析得到了冷却水温度和流量、气缸套和气缸盖温度变化对冷却水总传热流量的影响规律,以及管道尺寸、壁面粗糙度、冷却水流量对冷却水流动总阻力的影响规律。     

冰级船板式换热器流动传热分析及结构优化

采用数值模拟方法研究换热板结构对冰晶两相流换热机制和流动特性的影响。研究结果表明:波纹倾角β=60°、波纹深度h=4 mm、波纹间距λ=12 mm为所研究的换热器适用于海水-冰晶两相流的最佳值。利用宽通道对其进行结构优化设计,并采用相关试验数据验证。结果表明:宽通道间距为16 mm时,换热强度最大,流动阻力较小,可有效防止冰晶堵塞板内沟槽,且此时的换热效果和流动特性最佳,适合极地工况下冰晶两相流流动换热。     

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.     

垂直矩形窄通道启动过程壁温变化特性研究

以去离子水为介质，对竖直矩形窄通道在启动过程中壁面温度的变化规律进行了研究。将一次启动与二次启动时壁面温度的变化特性进行了对比，并改变入口温度，研究了入口温度对启动壁面温度的影响。结果表明：一次启动时壁面温度经过三个阶段，即急剧上升阶段、缓慢升高阶段、缓慢上升至最高壁面温度后又缓慢降至稳态饱和沸腾阶段；二次启动时产生的沸腾滞后现象较一次启动时明显；提高入口温度可增加饱和沸腾段，减少壁面温度的波动，在一定程度上可避免壁面温度过冲对换热器的损坏。     

宽带毫米波大规模MIMO系统中低复杂度波束域信道估计

针对宽带毫米波大规模MIMO系统信道估计精度低及实现复杂度较高的问题，在传统支撑检测方案的基础上提出一种基于Gauss-Seidel方法的串行支撑检测（GS-SSD）方案。该方案不使用共同支撑假设，参考串行干扰删除，将整体信道估计问题分解为一系列子问题，每个子问题仅考虑一个信道成分。同时，利用Gauss-Seidel方法近似高复杂度的矩阵求逆。仿真结果表明，相比于基于串行支撑检测（SSD）的方案， GS-SSD方案在将求逆复乘数降低一个数量级的同时可以取得接近SSD方案的信道估计性能。