Learning Forum

[Simon-Olivier]

Hi,
I would like your help since I am a stuck with this problem.
Context:
I solve a transient and nonlinear TE simulation with standard Newton-Raphson.
- With 2023 R1 version, the model is very stable and converges very well (symmetric global matrix)
- With 2023 R2 version, the model no longer converges (non- symmetric global matrix)
I noticed that:
- With 2023 R1 version , the model generates a symmetric global matrix
- With 2023 R2 version, the model generates a non-symmetrical global matrix, possibly brought about by the addition of new terms in elementary calculation
My question:
- What caused this non-symmetry in 2023 R2 version?
Is there an option somewhere that eliminates the consideration of this non-symmetry (to generate a symmetric global matrix)?
Thank you very much for your help.

[Ashish Khemka]

Hi Simon,

You can compare the input files - ds.dat for both the analysis. Right click on solution information and you will be able to see a file named ds.dat which is the input file to the solver. Comparing them will give you an idea on what is different in the setup for both the analysis.

Regards,

Ashish Khemka

[Simon-Olivier]

 

Hi, 

Thank you for the reply.

I compare the ds file for a very simple model and the only change is my node numerotation and I don’t know why (same number of node/elements/quality statistics…).

Also, the change in the global matrix formulation stays the same:

 

• With 2023 R1 version, tsymmetric global matrix
• With 2023 R2 version,non- symmetric global matrix

But this time, since the model is very simple, I can get a solution in the 2 cases.

Is there a reason for matrix symetric/non-simmetric?

Thank you for your help

 

[Ashish Khemka]

Hi Simon,

Thanks for sharing this. Let me check and I will let you know.

Regards,

Ashish Khemka

[dlooman]

Around that time we made the Seebeck effect strongly coupled.  This is probably the issue.  Set KEYOPT(2)=1 to go back to load vector coupling.  LNSRCH,ON is frequently helpful in these analyses.