Development of Two-Dimensional Non-Hydrostatic Wave Model Based on Central-Upwind Scheme

In this study, a two-dimensional depth-integrated non-hydrostatic wave model is developed. The model solves the governing equations with hydrostatic and non-hydrostatic pressure separately. The velocities under hydrostatic pressure conditions are firstly obtained and then modified using the biconjugate gradient stabilized method. The hydrostatic front approximation (HFA) method is used to deal with the wave breaking issue, and after the wave breaks, the non-hydrostatic model is transformed into the hydrostatic shallow water model, where the non-hydrostatic pressure and vertical velocity are set to zero. Several analytical solutions and laboratory experiments are used to verify the accuracy and robustness of the developed model. In general, the numerical simulations are in good agreement with the theoretical or experimental results, which indicates that the model is able to simulate large-scale wave motions in practical engineering applications.

Digital Estimation and Compensation of Analog Errors in Frequency-Interleaved ADCs

A novel digital compensation scheme for measuring, estimating and correcting linear weakly time-varying analog errors in frequency-interleaved analog-to-digital converters (FI-ADCs) is presented. This method features three important improvements over existing approaches: First, the Wigner–Ville distribution (WVD) is used to better estimate the nonstationary analog channel frequency response (ACFR) spectrum. Secondly, the estimated ACFR spectrum is approximated with a rational polynomial model using the [Formula: see text]-norm metric. The corresponding [Formula: see text]-norm minimization problem is solved using a primal-relaxed dual global optimization (PRD-GOP) method. Thirdly, the digital compensation circuitry is designed utilizing a preconditioned biconjugate gradient stabilized (BICGSTAB) algorithm that yields a computationally efficient solution. Numerical experimentations have been conducted and the outcomes validate the feasibility and superior performance of this proposed method.

Super-Resolution Ultrasound Imaging Based on a Fast Full-Waveform Solver

We propose a fast 2D full-waveform forward and inverse scattering solver to reconstruct ultrasonic speed and attenuation properties. The forward method is based on the volume integral equation, accelerated by the extended Born approximation and biconjugate-gradient fast Fourier transform method. The inverse method is based on the extended contrast source inversion. The research results show that our proposed method can fully unravel multiple scattering effects and achieve sub-wavelength resolutions. Numerical experiments indicate that the efficiency and robustness of the forward and inverse methods.

A comprehensive numerical model for double-layered porous air journal bearing at higher bearing numbers

Modeling air/gas lubricated double-layered porous journal bearing requires the solution of compressible Reynolds equation. It is observed that at higher bearing numbers, treatment of Reynolds equation with finite difference method using second-order central difference exhibits instabilities due to convective term dominance. To address such instabilities, Reynolds equation is discretized using finite volume and a third-order interpolation scheme to obtain variable values at grid point centers. Multistage Runge–Kutta method and biconjugate gradient stabilized method are used for solving governing equations at film and porous regions, respectively. Steady state and stability characteristics of finite double-layered porous air journal bearings considering Beavers–Joseph velocity slip at porous-film interface are obtained. Numerically stable results are obtained for bearing numbers up to 150 and feeding parameter values ranging from 0.01 to 10.

The Non–Symmetric s–Step Lanczos Algorithm: Derivation of Efficient Recurrences and Synchronization–Reducing Variants of BiCG and QMR

The Lanczos algorithm is among the most frequently used iterative techniques for computing a few dominant eigenvalues of a large sparse non-symmetric matrix. At the same time, it serves as a building block within biconjugate gradient (BiCG) and quasi-minimal residual (QMR) methods for solving large sparse non-symmetric systems of linear equations. It is well known that, when implemented on distributed-memory computers with a huge number of processes, the synchronization time spent on computing dot products increasingly limits the parallel scalability. Therefore, we propose synchronization-reducing variants of the Lanczos, as well as BiCG and QMR methods, in an attempt to mitigate these negative performance effects. These so-called s-step algorithms are based on grouping dot products for joint execution and replacing time-consuming matrix operations by efficient vector recurrences. The purpose of this paper is to provide a rigorous derivation of the recurrences for the s-step Lanczos algorithm, introduce s-step BiCG and QMR variants, and compare the parallel performance of these new s-step versions with previous algorithms.