Please, can someone answer to some dubts?
1- when computing a simulation, should one let it run without modify relaxation factors or is it possible/advised to modify them? It happens that changing a relaxation factor completely changes the convergence. But is it right to do so?
2- how can i understand when the simulation is converged? Sometimes it happens that although the residuals are low, the results have no physical sense. On the other hand, sometimes although the residuals are high macroscopic quantities ,pressure drop for example, do not change much through time steps and results seem to be quite good. Is there any way to be quite sure that simulation has reached convergence?
1) If you change the relaxation factors mostly two things can happen: a) the simulation converges faster b) the simulation diverges. I normally don't touch them, except if my simulation doesn't converge anyway. To your question: I don't see any problem in trying, but most of the time Fluent has pretty robust values as default.
2) Best thing is to find some relevant value that you can monitor during calculation. Let's say you are doing some RANS calculation, maybe a lift / drag coefficient of some (important) part inside your domain could be your monitoring value. What you actually take depends on your problem. Integral values are often a good and easy choice.
Thank you for your answer.
In effect what you replied is what i usually do but sometimes i'm not sure that it is right. For example, in some simulation i have to use very low values of relaxation factor to reach convergence, even lower than 0.1 . Is it correct?
I would like to ask you another question. Now i'm running a simulation, steady state incompressible flow in a quite complex geometry, with k-epsilon turbulence model and 1st order scheme. The mesh is unstructured, 240000 elements. It reached convergence (all residuals below 10^-5), y+ average value is around 30 (a bit low, i know, i would try to modify the mesh). The point is that the head loss i got is much lower than expected. I've tried to change k-epsilon inlet values and verified that head loss did not change. I tried to change the mesh to verify mesh dependence, but until now all other meshes i tried crashed before convergence.
I also tried to use Spalart-Allmaras model to see if something change, but the results i got were more or less the same of k-epsilon and still head loss under predicted.
Is there any way to understand if solution is good without having any experimental value to compare? I mean, i know what magnitude head loss should be, but i don't have local experimental values (i.e. velocity profile, pressure, etc..) to compare with CFD. How can i understand if solution is correct?
I don't know any good answer. But someone (like a mentor) told this: sometimes local values are not helpful. When it comes to k-e RANS modeling, global values can be predicted extremely good, but if you have a look at velocity profiles on a local scale you see completely wrong results. That's why I wouldn't see local values as a guarantee for getting good agreement also in the global values. Anyway, in your case even the global values are bad...
as you probably know relaxation factor is the ratio of the current calculated variable and the previous one, so basicly if you increase the relaxation factor your solution should converge faster (i don't mean the residuals) but generally it is convenient to keep relaxation factor relatively low in order to provide a consistent (non-divergent) solution.
it is certainly normal that when you decrease the relaxation factors residuals would remarkably decrease too, it is directly related with the how residual is computed, referring to the spalding's and patankar's journal paper at 1971 (A CALCULATION PROCEDURE FOR HEAT, MASS AND MOMENTUM TRANSFER IN THREE-DIMENSIONAL PARABOLIC FLOWS) residual for continuity let it be mass_imbalance = finite representation of contuinity equation.
if relaxation factor is too low, as you always proceed the numerical calculation almost with the previous calculated variable. your global mass imbalance will decrease but it does not mean that your finite equations have converged to the pde that you're solving.
what convergence really means is the fact that the dependent variables that you are solving each by using a transport equation(u,T,species etc) or a correction method (pressure), is not changing with respect to proceeding iterations. this is how you can judge that your solution has converged.
for your case, if it is too hard to judge convergence by tracing the dependent variables, you may consider to use the flux of a variable, to illustrate energy flux as (rho*u*cp*T) or standart deviation of a variable on a face.
hope this helps.
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