Hydromagnetic flow through uniform channel bounded by porous media

The combined effects of the magnetic field, permeable walls, Darcy velocity, and slip parameter on the steady flow of a fluid in a channel of uniform width are studied. The fluid flowing in the channel is assumed to be homogeneous, incompressible, and Newtonian. Analytical solutions are constructed for the governing equations using Beavers-Joseph slip boundary conditions. Effects of the magnetic field, permeability, Darcy velocity, and slip parameter on the axial velocity, slip velocity, and shear stress are discussed in detail. It is shown that the Hartmann number, Darcy velocity, porous parameter, and slip parameter play a vital role in altering the flow and in turn the shear stress.

Analytical Modeling of Threshold Voltage for Double-Gate MOSFET Fully Comprising Quantum Mechanical Effects

The analytical solutions to 1D Schrdinger equation (in depth direction) in double gate (DG) MOSFETs are derived to calculate electron density and threshold voltage.The non uniform potential in the channel is concerned with an arbitrary depth so that the analytical solutions agree well with numerical ones.Then,an implicit expression for electron density and a closed form of threshold voltage are presented fully comprising quantum mechanical (QM) effects.This model predicts an increased electron density with an increasing channel depth in subthreshold region or mild inversion region.However,it becomes independent on channel depth in strong inversion region,which is in accordance with numerical analysis.It is also concluded that the QM model,which barely considers a box like potential in the channel,slightly over predicts threshold voltage and underestimates electron density,and the error increases with an increasing channel depth or a decreasing gate oxide thickness.

Multi-Task Deep Learning Based Hybrid Precoding for mmWave Massive MIMO System

Due to the different signal-to-noise ratio(SNR)of each subchannel,the bit error rate(BER)of hybrid precoding based on singular value decomposition(SVD)decreases.In this paper,we propose a multi-task learning based precoding network(PN)model to solve the BER loss problem caused by SVD based hybrid precoding under imperfect channel state information(CSI).Specifically,we firstly generate a dataset including imcomplete CSI input channel matrix and corresponding output labels to train the PN model.The output labels are designed based on uniform channel decomposition(UCD)which decomposes the channel into multiple subchannels with same gain,while the vertical-bell layered space-time structure(V-BLAST)signal processing technology is combined to eliminate the inner interference of the subchannels.Then,the PN model is trained to design the analog and digital precoding/combining matrix simultaneous.Simulation results show that the proposed scheme has only negligible gap in spectrum efficiency compared with the fully digital precoding,while achieves better BER performance than SVD based hybrid precoding.

STUDY OF NONLINEAR LONG WAVE APPOXIMATION IN UNIFORM CHANNELS VIA HAMILTONIAN STRUCTURE

This peper studies the nonlinear wave theory in shallow water via the Hamiltonian structure. The principal is the surface wave evolution on water contained in uniform channels. The Ploper Hamiltonian appoximating scheme for the more general case of waves that undergo transverse variations in amplitude in the course of longitudinal propagations is constructed. Some solutions for channels with different cross-sections,especially,the rectangular cross-section, are presented to elucidate the main features of the approxiamting scheme for the problem of interest. The obtained results shows that the nonlinear approximation of wave evolution in channels depends not only on water depth but also on a parameter determined by the geometric shape Of the channel.