Hi, everyone,
I encounted one problem concerning the S parameter simulation frequency step.
To check the simulation with experimental results, I have done two adaptive sweep type simulations consecutively, with all other parameters being the same.
1) frequency range 0.1~8GHz. Results agree quite well, but 0.7~0.9GHz range has relatively big difference. So I
change and narrow down to the desired range, and (2) simulation is conducted.
2) frequency range 0.7~0.9GHz.
In the rational fitted raw S parameter results (touchstone file), I found out that, the case (1) has coarser discrete points
than case (1). Which puzzled me quite a bit, as I thought the narrowed down frequency range would result in denser points.
Then, I tried to run the linear discrete sweep type rather than adaptive sweep type in case (2) simulation, however, due to memory problem, simulation failed.
My questions are
(a) In the adaptive sweep type, if I want to get denser points result, what should I do? Reduce the delta error, or increase the sample points limit? Is it possible to set the desired frequency points in the adaptive sweep?
(b) In the discrete sweep type, using iterative rather than direct solver would consume less memory, are there any
other solutions to reduce the memory consumption?
Thank you very much!
Yours,
Yiliu
I encounted one problem concerning the S parameter simulation frequency step.
To check the simulation with experimental results, I have done two adaptive sweep type simulations consecutively, with all other parameters being the same.
1) frequency range 0.1~8GHz. Results agree quite well, but 0.7~0.9GHz range has relatively big difference. So I
change and narrow down to the desired range, and (2) simulation is conducted.
2) frequency range 0.7~0.9GHz.
In the rational fitted raw S parameter results (touchstone file), I found out that, the case (1) has coarser discrete points
than case (1). Which puzzled me quite a bit, as I thought the narrowed down frequency range would result in denser points.
Then, I tried to run the linear discrete sweep type rather than adaptive sweep type in case (2) simulation, however, due to memory problem, simulation failed.
My questions are
(a) In the adaptive sweep type, if I want to get denser points result, what should I do? Reduce the delta error, or increase the sample points limit? Is it possible to set the desired frequency points in the adaptive sweep?
(b) In the discrete sweep type, using iterative rather than direct solver would consume less memory, are there any
other solutions to reduce the memory consumption?
Thank you very much!
Yours,
Yiliu
The best way to force more points in an adaptive sweep is to add a linear sweep segment to the same simulation (you can have multiple sweeps defined in a single simulation).
One thing to watch out for is to make sure the mesh is refined at the proper frequency. The default is the highest frequency in the sweep, which is usually good for broadband applications, but not the best for applications where there are resonances. In your case you may have refined the mesh at 8GHz (the highest frequency in your first simulation). Then when you ran the next simulation (0.7-0.9GHz) the mesh may have been refined at 0.9GHz (assuming you left the mesh refinement settings at the default). But if this was near a resonance the optimum mesh might be quite different (and much more dense) than the first mesh at 8GHz, and this is what may have caused you to run out of memory in the second simulation. But this is probably a better mesh to use if you want to accurately capture a resonance. So in general you may want to try the mesh refinement frequency setting "Chosen automatically after initial pass", which will look for resonances during the initial mesh refinement pass and then use a more appropriate frequency to refine the mesh than the highest frequency.
If you are running out of memory during mesh refinement, the best approach is to switch to the iterative solver (which by the way is much faster in recent releases and is now multithreaded). You could also increase delta error but this will reduce your accuracy of course.
Hope this helps,
Marc