Different Types of Current Distribution
Display
On the MGRID, we
can display 6-types of current distribution. What are the meanings of the
different types? This appendix explains the differences.
At any location,
the time-harmonic current density can be described as a complex vector:
J(x,y,z) = Jx x
+ Jy y
+ Jz z (L-1)
where x, y and z are the unit vectors.
Jx = Jxr + j Jxi (L-2)
Jy = Jyr + j Jyi (L-3)
Jz = Jzr + j Jzi (L-4)
Then, we can get,
J(x,y,z) = ( Jxr x
+ Jyr y + Jzr z ) + j ( Jxi x + Jyi y + Jzi z
) (L-5)
J(x,y,z) = Jmr r + j Jmi i (L-6)
where r and i are the unit vectors for the real
and imaginary parts, respectively
Jmr = Ö ( Jxr2 + Jyr2 + Jzr2 ) (L-7)
Jmi = Ö ( Jxi2 + Jyi2 + Jzi2 ) (L-8)
r = ( Jxr x + Jyr y
+ Jzr z ) / Jmr (L-9)
I = ( Jxi x + Jyi y
+ Jzi z ) / Jmr (L-10)
At a specific time, the time-harmonic current density is,
J(x,y,z, t) = Re[ J(x,y,z) exp(jwt) ] = r
Jmr cos( wt ) - i Jmi sin( wt) (L-11)
Equation (L-11) is
the actual current density at a specific location at a specific time. Clearly,
both the value and direction of J(x,y,z, t) are changing with time.
Table L-.1 shows the correspondence between the current display functions and
the quantities.
Table L-1 Correspondence between the current display functions and
the quantities
|
Display Type
|
Quantity
|
Display Features
|
|
Average Current
Distribution
|
Ö ( Jmr2 + Jmi2 )
|
Shows the average intensity
at each location
|
|
Vector Current
Distribution
|
J(x,y,z, t)
|
Shows the direction and
intensity at specific location and time as vectors on arrows.
|
|
Average and
Vector Current Distribution
|
Ö ( Jmr2 + Jmi2 )
and J(x,y,z,
t)
|
Shows the average intensity
as color on polygons and direction of current density at a specific time with
vectors on arrows.
|
|
Scalar Current
Distribution Animation
|
|J(x,y,z,
t)|
|
Shows the current density
at different locations at different time.
|
|
Vector Current
Distribution Animation
|
J(x,y,z, t)
|
Shows the direction and
intensity at different locations at different time.
|
|
Scalar and Vector
Current Distribution Animation
|
|J(x,y,z,
t)| and J(x,y,z, t)
|
Shows the direction and
intensity at different locations at different time.
|
. Rectangular Mesh Versus Triangular Mesh
IE3D uses a non-uniform, mixed rectangular and triangular meshing
scheme. Usually, rectangular cells are efficient for regular shaped portion of
a structure. Each rectangular cell is equivalent to 2 triangular cells.
Triangular cells are flexible on modeling irregular shaped portion of a
structure. It can fit the irregular boundary easily (see Figure M.1). Some
people claimed that triangular cells could not yield accurate results because
of the zigzag in the meshing. Such a claim is certainly not true, at least for
IE3D. In this appendix, we will show that modeling using triangular cells is as accurate as modeling using rectangular
cells. We will also demonstrate the efficiency of rectangular cells.
Figure
M.1 Comparison between triangular and rectangular cells.
A simple
rectangular patch antenna is used as our example. The structure using
rectangular mesh is saved in c:\ie3d\samples\rcell.geo
and the structure using triangular mesh is saved in c:\ie3d\samples\tcell.geo. They are identical except the difference
in meshing. The meshed structure is compared in Figure M.2.
Figure
M.2 Meshed structure using rectangular cells (rcell.geo) and triangular cells
(tcell.geo).
Table M.1 and
Figure M.3 show the comparison between the simulation results using rectangular
cells (c:\ie3d\samples\rcell.geo)
and triangular cells (c:\ie3d\samples\tcell.geo).
They are almost identical on the Smith Chart. In fact, there is a slightly
frequency shift due to the difference in the meshing. Certainly, the triangular
meshing scheme takes more memory and time to simulate the structure.
Table M.1 The comparison between rectangular cells and triangular
cells.
|
|
Number
of Cells
|
Number
of Unknowns
|
Memory
Required
|
Simulation
Time Per Frequency
|
|
Rectangular
Mesh (c:\ie3d\samples\rcell.geo)
|
126
|
225
|
2 M
|
0.6
seconds
|
|
Triangular
Mesh
(c:\ie3d\samples\tcell.geo)
|
248
|
347
|
4 M
|
2
seconds
|
Figure M.3 The comparison between rectangular meshing and triangular
meshing.
. Uniform Grid Versus Non-Uniform Grid
We have discussed the theoretical comparison between uniform grid
and non-uniform grid in Section 2 of Chapter 1. We will provide an actual
structure for comparison between using the uniform grid and non-uniform grid.
The structure is derived from the geometry saved in c:\ie3d\samples\lpass.geo. The structure in lpass.geo can be best fitted into a uniform grid with grid size of
1 mil. The problem we encountered is that we cannot simulate the structure lpass.geo using a uniform grid of size
1 mil on the IE3D with even 256 M RAM without swapping the memory. What we can
do is to first shorten the feed-line and then adjust the geometry to fit it
into a uniform grid of 2 mils. In such a case, we can solve the problem using
about 32 M RAM without swapping. We simulated the structure using the following
3 schemes:
1. Non-Uniform Grid without
Edge Cells:
The structure
is saved into c:\ie3d\samples\lpass1.geo
and shown in Figure N.2a.
2. Non-Uniform Grid with
Edge Cells for accuracy enhancement:
The structure
is saved into c:\ie3d\samples\lpass2.geo
and shown in Figure N.2b.
3. Uniform Grid Structure:
The structure
is saved into c:\ie3d\samples\lpass3.geo
and shown in Figure N.2c.
Comparison between the three schemes is shown in Table N.1. The simulation
result is shown in Figure N.1. It is interesting to note that the results
between Non-Uniform Grid with Edge Cells and Uniform Grid Structure compare
very well. However, the Non-Uniform Grid with Edge Cells uses much less memory
and simulation time to solve the problem. We still get close result without
adding the edge cells. Certainly, adding the edge vertices to create small edge
cells will improve the simulation accuracy.
It is also interesting to note that the adjusted structure (lpass1.geo, lpass2.geo and lpass3.geo) yield quite different
results from the original structure in c:\ie3d\samples\lpass.geo.
Our conclusion on the uniform and non-uniform grids is:
Figure
N.1 The comparison of the results from uniform grid, non-uniform grid with or
without edge cells.
1. Non-uniform grid scheme
is much more efficient than uniform grid scheme.
2. Non-uniform grid with
edge cells enhancement is at of the same accuracy of the uniform grid scheme
when the edge cell size of the non-uniform grid is the same as that for the
uniform grid.
3. Non-uniform grid without
edge cells enhancement yields reasonably accurate result with extremely high
efficiency.
4. Fitting structure into a
uniform grid may create significant error.
5. Uniform grid is
extremely low efficiency and it is not suitable for large circuit analysis.
Table N.1 Comparison
between Uniform Grid and Non-Uniform
|
|
Number
of Cells
|
Number
of Unknowns
|
Memory
Required
|
Simulation
Time Per Frequency
|
|
Non-Uniform
without AEC (lpass1.geo)
|
141
|
180
|
2 M
|
1
seconds
|
|
Non-uniform
with AEC (lpass2.geo)
|
467
|
762
|
5 M
|
9
seconds
|
|
Uniform
Grid (lpass3.geo)
|
919
|
1556
|
25 M
|
60
seconds
|
Figure N.2 The meshed structure using uniform and non-uniform
schemes.
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