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EEE 431 Computational Methods in Electrodynamics

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EEE 431 Computational Methods in Electrodynamics Lecture 6 By Dr. Rasime Uyguroglu Rasime.uyguroglu_at_emu.edu.tr – PowerPoint PPT presentation

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Title: EEE 431 Computational Methods in Electrodynamics


1
EEE 431Computational Methods in Electrodynamics
  • Lecture 6
  • By
  • Dr. Rasime Uyguroglu
  • Rasime.uyguroglu_at_emu.edu.tr

2
FINITE DIFFERENCE METHODS (cont).
3
FINITE DIFFERENCE METHODS (cont).
  • Finite Differencing of Hyperbolic PDEs
  • Consider the wave equation

4
FINITE DIFFERENCE METHODS (cont).
  • Using central difference formula the wave
    equation may be approximated as

5
FINITE DIFFERENCE METHODS (cont).
  • Substituting
  • Let

6
FINITE DIFFERENCE METHODS (cont).
  • Example Solve the wave equation
  • Subject to the boundary conditions,
  • And the initial conditions

7
Finite Difference Method
  • Take r1,
  • For j0,

8
Finite Difference Method
  • Substitute to get the starting formula

9
Finite Difference Method
  • Since u1, r1, chose,
  • Solve the problem for since it is
    symmetric. See the C code.

10
Finite Difference Method
  • Finite Differencing of Elliptic PDEs. Consider
    the two dimensional Poissons Equation

11
Finite Difference Method
  • Central difference approximation for the partial
    derivatives

12
Finite Difference Method
  • Where,
  • Assume
  • FD approximation of the Poissons equation after
    simplification

13
Finite Difference Method
  • Gives
  • Or

14
Finite Difference Method
  • When the source term vanishes, the Poissons
    equation leads to the Laplaces equation. Thus
    for the same mesh size h

15
Finite Difference Method
  • The application of the finite difference method
    to elliptic PDEs often leads to a large system of
    algebraic equations to be solved.
  • Solution of such equations is a major problem.
    Band matrix and iterative methods are commonly
    used to solve the system of equations.

16
Finite Difference Method
  • Band Matrix Method
  • Notice that only nearest neighboring nodes affect
    the value of at each node.
  • Application of the FD equations results in a set
    of equation such that

17
Finite Difference Method
  • Where is a sparse matrix (it has many
    zeros) , is the column matrix consisting
    of the unknown values, and
  • is the column matrix containing the known
    values of . So

18
Accuracy and Stability FD Solutions
  • Accuracy is the closeness of the approximate
    solution to the exact solutions.
  • Stability is the requirement that the scheme does
    not increase the magnitude of the solution with
    increase in time.

19
Accuracy and Stability FD Solutions
  • Unavoidable errors in numerical solution of
    physical problems
  • modeling errors,
  • truncation (or discretization) errors,
  • round-off errors

20
Accuracy and Stability FD Solutions
  • Modeling errors Several assumptions are made for
    obtaining the mathematical model. i.e. nonlinear
    system may be represented by a liner PDE.

21
Accuracy and Stability FD Solutions
  • Truncation errors, arise from the fact that in
    numerical analysis we can deal only with finite
    number of terms of a series.

22
Accuracy and Stability FD Solutions
  • Truncation errors may be reduced
  • By using finer meshes. i.e. smaller time and
    space step sizes and more number of points.
  • By using a large number of terms in the series
    expansion of derivatives.

23
Accuracy and Stability FD Solutions
  • Round-off Errors, are due to finite precision of
    computers.
  • May be reduced by using double precision.

24
Accuracy and Stability FD SolutionsError as a
function of a mesh size
25
Accuracy and Stability FD Solutions
  • To determine whether the FD scheme is stable,
    define an error, , which occurs at time
    step n, assuming a single independent variable.
    Define the amplification of this error at time
    step n1 as
  • Where is known as amplification factor.

26
Accuracy and Stability FD Solutions
  • For the stability of the difference scheme it is
    required that the above equation satisfies
  • or

27
2D Potential Distribution in a Discrete
Inhomogeneous Dielectric
  • The relevant equation is

28
2D Potential Distribution in a Discrete
Inhomogeneous Dielectric
  • Divide the domain into a grid.

29
2D Potential Distribution in a Disceat
Inhomogeneous Dielectric
  • And

30
2D Potential Distribution in a Discrete
Inhomogeneous Dielectric
  • So,

31
2D Potential Distribution in a Discreat
Inhomogeneous Dielectric
  • Similarly
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