• Title/Summary/Keyword: D1%2FD2 domain

Search Result 4, Processing Time 0.023 seconds

2D Crank-Nicolson FDTD Method Based on Isotropic-Dispersion Finite Difference Equation for Lossy Media (손실 매질에 대한 Isotropic-Dispersion 유한 차분식의 2D Crank-Nicolson FDTD 기법)

  • Kim, Hyun;Koh, Il-Suek;Yook, Jong-Gwan
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
    • /
    • v.21 no.7
    • /
    • pp.805-814
    • /
    • 2010
  • The Crank-Nicolson isotropic-dispersion finite difference time domain(CN ID-FDTD) scheme is proposed based on isotropic-dispersion finite difference(ID-FD) $equation^{[1],[2]}$. The dispersion relation of CN ID-FDTD is derived for lossy media by solving the eigenvalue problem of iteration matrix in spatial spectral domain, in addition, the weighting factors and scaling factors of the CN ID-FDTD scheme are presented for low dispersion error. The CN ID-FDTD scheme makes the dispersion error drastically reduced and shows accurate numerical results compared to the conventional Crank-Nicolson FDTD method.

2-D Modeling of Electromagnetic Waves for the Probing of Concrete (콘크리트 내부 탐사를 위한 전자기파의 2차원 모델링)

  • 조윤범;임홍철
    • Proceedings of the Computational Structural Engineering Institute Conference
    • /
    • 2000.10a
    • /
    • pp.18-23
    • /
    • 2000
  • The radar method is becoming one of the major nondestructive testing (NDT) techniques for concrete structures. Numerical modeling of electromagnetic wave is needed to analyze radar measurement results and to study the influence of measurement parameters on the radar measurements. Finite difference-time domain (FD-TD) method is used to simulate electromagnetic wave propagation through concrete specimens. Three concrete specimens with a 19.1 mm rebar embedded at 40 mm, 60 mm, and 80 mm depth are modeled in 3-dimension. As results, 2-D image processing scheme of modeling data has been developed and applied to the imaging of steel bars inside concrete.

  • PDF

Modeling of Active Layer and Injection-locking Characteristics in Polarized and Unpolarized Fabry-Perot Laser Diodes (편광 또는 무편광 패브리-페롯 레이저 다이오드의 활성층 및 주입 잠금 동작 특성 모델링)

  • Chung, Youngchul;Yi, Jong Chang;Cho, Ho Sung
    • Korean Journal of Optics and Photonics
    • /
    • v.23 no.1
    • /
    • pp.42-51
    • /
    • 2012
  • In this paper, injection-locking characteristics versus active layer structures in Fabry-Perot laser diodes (FP-LD) are compared. TE and TM gain spectra and peak gains versus carrier density in polarized and unpolarized multiple quantum well structures and in an unpolarized bulk structure are calculated. The calculated gain parameters are applied to a time-domain large-signal model to simulate the injection-locking characteristics. The results show that RIN in unpolarized FD-LDs is about 3 dB lower than that in a polarized FP-LD and that the eye characteristics of the unpolarized FP-LD are much better than those of the polarized FP-LD.

Acceleration of computation speed for elastic wave simulation using a Graphic Processing Unit (그래픽 프로세서를 이용한 탄성파 수치모사의 계산속도 향상)

  • Nakata, Norimitsu;Tsuji, Takeshi;Matsuoka, Toshifumi
    • Geophysics and Geophysical Exploration
    • /
    • v.14 no.1
    • /
    • pp.98-104
    • /
    • 2011
  • Numerical simulation in exploration geophysics provides important insights into subsurface wave propagation phenomena. Although elastic wave simulations take longer to compute than acoustic simulations, an elastic simulator can construct more realistic wavefields including shear components. Therefore, it is suitable for exploration of the responses of elastic bodies. To overcome the long duration of the calculations, we use a Graphic Processing Unit (GPU) to accelerate the elastic wave simulation. Because a GPU has many processors and a wide memory bandwidth, we can use it in a parallelised computing architecture. The GPU board used in this study is an NVIDIA Tesla C1060, which has 240 processors and a 102 GB/s memory bandwidth. Despite the availability of a parallel computing architecture (CUDA), developed by NVIDIA, we must optimise the usage of the different types of memory on the GPU device, and the sequence of calculations, to obtain a significant speedup of the computation. In this study, we simulate two- (2D) and threedimensional (3D) elastic wave propagation using the Finite-Difference Time-Domain (FDTD) method on GPUs. In the wave propagation simulation, we adopt the staggered-grid method, which is one of the conventional FD schemes, since this method can achieve sufficient accuracy for use in numerical modelling in geophysics. Our simulator optimises the usage of memory on the GPU device to reduce data access times, and uses faster memory as much as possible. This is a key factor in GPU computing. By using one GPU device and optimising its memory usage, we improved the computation time by more than 14 times in the 2D simulation, and over six times in the 3D simulation, compared with one CPU. Furthermore, by using three GPUs, we succeeded in accelerating the 3D simulation 10 times.