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排序方式: 共有10000条查询结果,搜索用时 16 毫秒
1.
Khaled Al-Farhany Mohammed A. Alomari Ahmed Al-Saadi Ali Chamkha Hakan F. Öztop Wael Al-Kouz 《亚洲传热研究》2022,51(2):1691-1710
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 Nuavg rises as the Ri rise, the maximum Nuavg = 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 Nuavg increased by 8.44% when the volume fraction of nanofluid increased from (ϕ = 0–0.05). 相似文献
2.
《Geotextiles and Geomembranes》2022,50(6):1230-1243
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. 相似文献
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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). 相似文献
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针对传统基于贝叶斯模型的显著性检测算法存在准确率不理想的问题,提出了一种基于多尺度的贝叶斯模型显著性检测算法。通过超像素分割算法(SLIC)将原图分割成不同尺度的超像素,根据超像素边界信息得到背景种子,进而通过距离计算和多尺度融合得到背景先验;对原图进行颜色增强,采用Harris算子对增强图进行检测角点求得凸包,融合不同尺度下的超像素得到凸包先验;融合背景先验和凸包先验得到最终先验;利用颜色直方图和凸包计算似然概率;将最终先验和似然概率通过贝叶斯模型计算显著图。在公开数据集MSRA1000、ECSSD上与多种传统算法进行准确率和召回率对比,该算法有更好的表现。 相似文献
6.
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%。 相似文献
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In the task of skeleton-based action recognition, CNN-based methods represent the skeleton data as a pseudo image for processing. However, it still remains as a critical issue of how to construct the pseudo image to model the spatial dependencies of the skeletal data. To address this issue, we propose a novel convolutional neural network with adaptive inferential framework (AIF-CNN) to exploit the dependencies among the skeleton joints. We particularly investigate several initialization strategies to make the AIF effective with each strategy introducing the different prior knowledge. Extensive experiments on the dataset of NTU RGB+D and Kinetics-Skeleton demonstrate that the performance is improved significantly by integrating the different prior information. The source code is available at: https://github.com/hhe-distance/AIF-CNN. 相似文献
10.
《等离子体科学和技术》2020,22(8):85001
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. 相似文献