Large-scale edge waves generated by a moving atmospheric pressure

Long waves generated by a moving atmospheric pressure distribution, associated with a storm, in coastal region are investigated numerically. For simplicity the moving atmospheric pressure is assumed to be moving only in the alongshore direction and the beach slope is assumed to be a constant in the on-offshore direction. By solving the linear shallow water equations we obtain numerical solutions for a wide range of physical parameters, including storm size （2a）, storm speed （U）, and beach slope （a）. Based on the numerical results, it is determined that edge wave packets are generated if the storm speed is equal to or greater than the critical velocity, Ucr, which is defined as the phase speed of the fundamental edge wave mode whose wavelength is scaled by the width of the storm size. The length and the location of the positively moving edge wave packet is roughly Ut/2 〈 y 〈 Ut, where y is in the alongshore direction and t is the time. Once the edge wave packet is generated, the wavelength is the same as that of the fundamental edge wave mode corresponding to the storm speed and is independent of the storm size, which can, however, affect the wave amplitude. When the storm speed is less than the critical velocity, the primary surface signature is a depression directly correlated to the atmospheric pressure distribution.

Comparison of linear and nonlinear extreme wave statistics

An extremely large（＂freak＂） wave is a typical though rare phenomenon observed in the sea. Special theories（for example, the modulation instability theory） were developed to explain mechanics and appearance of freak waves as a result of nonlinear wave-wave interactions. In this paper, it is demonstrated that the freak wave appearance can be also explained by superposition of linear modes with the realistic spectrum. The integral probability of trough-to-crest waves is calculated by two methods： the first one is based on the results of the numerical simulation of a wave field evolution performed with one-dimensional and two-dimensional nonlinear models.The second method is based on calculation of the same probability over the ensembles of wave fields constructed as a superposition of linear waves with random phases and the spectrum similar to that used in the nonlinear simulations. It is shown that the integral probabilities for nonlinear and linear cases are of the same order of values

Numerical modeling of a linear photonic system for accurate and efficient time-domain simulations

In this paper, a novel modeling and simulation method for general linear, time-invariant, passive photonic devices and circuits is proposed. This technique, starting from the scattering parameters of the photonic system under study, builds a baseband equivalent state-space model that splits the optical carrier frequency and operates at baseband, thereby significantly reducing the modeling and simulation complexity without losing accuracy.Indeed, it is possible to analytically reconstruct the port signals of the photonic system under study starting from the time-domain simulation of the corresponding baseband equivalent model. However, such equivalent models are complex-valued systems and, in this scenario, the conventional passivity constraints are not applicable anymore. Hence, the passivity constraints for scattering parameters and state-space models of baseband equivalent systems are presented, which are essential for time-domain simulations. Three suitable examples demonstrate the feasibility, accuracy, and efficiency of the proposed method.

Parallel Implementation of Linear Algebra Problems on Dawning-1000

In this paper, some parallel algorithms are described for solving numerical linear algebra problems on Dawning-1000. They include matrix multiplication, LU factorization of a dense matrix, Cholesky factorization of a symmetric matrix, and eigendecomposition of symmetric matrix for real and complex data types. These programs are constructed based on fast BLAS library of Dawning-1000 under NX environment.Some comparison results under different parallel environments and implementing methods are also given for Cholesky factorization. The execution time, measured performance and speedup for each problem on Dawning-1000 are shown. For matrix multiplication and LU factorization, 1.86GFLOPS and 1.53GFLOPS are reached.