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The discretization in time for FDTD is performed in a leap frog manner by application of a temporally shifted updating for E- and H-field components as shown in Fig. Each three E- and H-field components are assigned to a node i, j, k within the three dimensional (3-D) FDTD grid. The fields are located in a way in which each E component is surrounded by four H components and vice versa, which leads to a spatially coupled system of field circulations corresponding to the law of Faraday and Ampere. 2 depicts the position of the electric (yellow) and magnetic (green) field components for each primary and secondary Yee cell, respectively, allocated within the staggered cartesian grid. The FDTD algorithm proposed by Yee is based on a description of the temporarily coupled system as described in equations 2 and 3 on the basis of a finite central difference approximation. The exponentially increasing availability of computational power has made FDTD the most popular numerical method for a broad range of applications and has resulted in the release of several public and commercial FDTD-based simulation platforms.īy assuming a spatial environment without any electric or magnetic sources, the relationsĮnable a definition of the time dependent Maxwell’s curl equations in differential form as follows: 1, approximately 4500 scientific papers related to FDTD have been published, mainly from the late 90s to the present (1999-2001: counts not complete). Within the last two decades, FDTD gained rapidly increasing interest, mainly in electromagnetics (EM), for the simulation of complex and largely inhomogeneous structures due to its straightforward and explicit approach. The Finite-Difference Time-Domain (FDTD) method is based on a spatial and temporal discretization of Maxwell’s equations, commonly within a rectilinear cartesian grid originally proposed by Yee in 1966. The Finite-Difference Time-Domain (FDTD) Technique Introduction to FDTD