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Posted by on Jul 29, 2013 in Electromagnetism, Finite-Difference Time-Domain Method | 0 comments

The Finite-Difference Time-Domain Method

There are numerous ways to solve problems in computational electromagnetics. While all are feasible, one method has seen a meteoric rise in popularity since its inception in 1966: the finite-difference time-domain method (FDTD).

electromagnetic fieldsFDTD is a method of solving problems in computational electromagnetics that uses Maxwell’s equations and derivations of them to illustrate the behavior of electromagnetic fields around an object. In these equations, space and time are combined into spacetime, rather than examined as two separate entities. This means that in a FDTD problem, for any given moment in time, there is only one possible arrangement of the electromagnetic fields surrounding an object.

The finite-difference time-domain method compares the change in an electronic field in time against a change in a magnetic field across space. Conversely, it also examines the changes in a magnetic field along an analogous electronic field in space. By incrementally stepping through individual moments in time while measuring the strengths of electromagnetic fields along the space, the FDTD method creates a model of the electromagnetic fields acting on an object.

The FDTD method is performed on a given space and equations are elegant enough to account for the properties of the materials being examined, such as their electrical conductivity, permittivity, and permeability. When put through a computer, the method essentially runs a simulation of the electromagnetic fields of an object. This creates a lot of data that can be mined and visualized. It’s even possible to simulate the effects of the addition of an electromagnetic pulse to the model, making the method invaluable to engineers working with antennae and other electromagnetic receivers.

While FDTD has gained a lot of popularity for its intuitiveness and ability to outline huge models as they change through time, it does have its drawbacks. FDTD requires a great deal of preparatory planning on the system. It calls for every aspect of the item upon which the simulation is to be run to be modeled at a degree precise enough to account for tiny differences in electromagnetic wavelengths. FDTD may also take more computing time than other methods, especially depending on the shape of the object being examined.

The Future Data Testing Department uses this method as well as others in its data acquisition, visualization, and machine learning projects. Of course, this is nowhere near a full discussion of the complexities of the finite-difference time-domain method, but we believe it’s a reasonable overview of how and why we employ it.

 

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