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An Introduction to Computational Electromagnetics using FDTD

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If H is evaluated at the half-integer steps while E is evaluated at the integer ... have a PDE with constant coefficients and a constant inhomogeneous term. ... – PowerPoint PPT presentation

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Title: An Introduction to Computational Electromagnetics using FDTD


1
  • An Introduction to Computational Electromagnetics
    using FDTD
  • R. E. Diaz

2
Finite Difference Time Domain is a Partial
Differential Equation method
  • The DDSURF/SUB/FILM family is an Integral
    Equation method.
  • Advantage Need to dicretize only scatterer.
  • If The Green function of the environment is
    known.
  • Disadvantage Must invert a huge matrix.
    Unstable if egtgt1.
  • PDE methods
  • Advantage No Green function, no inversion.
  • If You have time (computing power) if egtgt1.
  • Disadvantage Must discretize all of space.

3
FDTD encodes Maxwells curl equations over all
space.
  • Maxwells first curl equation
  • where e is in general an operator e(w)
  • Take its Fourier Transform
  • Thus,
  • And

4
This is an Initial Value PDE problem that can be
solved from time t to tdt
  • To solve the inhomogeneous PDE in discretized
    time, set up a leapfrog scheme
  • If H is evaluated at the half-integer steps while
    E is evaluated at the integer steps, the curl
    acts as a source term.

5
We therefore have a PDE with constant
coefficients and a constant inhomogeneous term.
  • We have two alternatives
  • (a) solve the initial value problem (gives an
    exponential characteristic solution) or
  • (b) turn the equation into finite difference form
    using the fundamental theorem of calculus
  • But at what time must E(?) be evaluated?

6
For the equation to be valid at the same instant
everything must be evaluated at the half-integer
time step.
  • The time derivative of E is clearly evaluated at
    the half-integer step.
  • So is the curl of H.
  • Therefore so must be E(?)(E(tdt)E(t))/2

7
In the same way, Maxwells second curl equation
is reduced to an update equation.
  • Now, since curl of E is evaluated at t, and the
    time derivative of H also occurs at t,
  • H(?)(H(tdt/2)H(t-dt/2))/2
  • And
  • becomes

8
Thus, we have a leapfrog algorithm, from H to E
and from E to H, and back again...
  • Now lets talk about discretization in space.
  • The Yee lattice intercalates E and H in space,
    making the definitions of the curl operators
    straight-forward.
  • The Yee unit cell
  • At the (i,j,k) point E is on the edges, H is on
    the faces.

9
Consider the x component of the curl of H
10
Similarly, the x component of the curl of E...
11
The FDTD algorithm marches E and H in time
throughout the grid the way an EM wave propagates.
  • All interactions in materials and satisfaction of
    boundary conditions across material boundaries
    occur automatically.
  • Because the computational domain must be
    truncated, need Absorbing Boundary Conditions.
  • The finite grid size introduces grid dispersion
    that limits the upper frequency at which a
    Fourier Transform of the time domain result is
    valid.
  • The time domain solution is multi-frequency by
    nature. Not necessarily overkill because it can
    be used to discern phenomena.

12
Consider a 108 nm Si sphere sitting on a 75 nm
SiO2 film on top of Si
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16
Conclusions and Future Work
  • FDTD is a very stable PDE computational
    electromagnetics tool that is rapidly becoming a
    standard in Optics as well as RF research.
  • It serves well as a complement to the IE method
    family of codes DDSURF/SUB/FILM.
  • The latter can be extremely fast for moderate
    scenes But when material parameters are extreme
    and/or the matrix just cannot be inverted, all
    that FDTD needs is memory and time.
  • Ongoing work to improve its efficiency for
    optical scattering focuses on dispersive material
    modeling, the absorbing boundary conditions, and
    the input and output of incident plane waves.
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