Hi Jed, I will come back with answers to all of your questions at some point. I mostly just deal with MOOSE users who come to me and tell me their solve is converging slowly, asking me how to fix it. So I generally assume they have built an appropriate mesh and problem size for the problem they want to solve and added appropriate turbulence modeling (although my general assumption is often violated).
> And to confirm, are you doing a nonlinearly implicit velocity-pressure solve? Yes, this is our default. A general question: it seems that it is well known that the quality of selfp degrades with increasing advection. Why is that? On Wed, Jun 7, 2023 at 8:01 PM Jed Brown <[email protected]> wrote: > Alexander Lindsay <[email protected]> writes: > > > This has been a great discussion to follow. Regarding > > > >> when time stepping, you have enough mass matrix that cheaper > preconditioners are good enough > > > > I'm curious what some algebraic recommendations might be for high Re in > > transients. > > What mesh aspect ratio and streamline CFL number? Assuming your model is > turbulent, can you say anything about momentum thickness Reynolds number > Re_θ? What is your wall normal spacing in plus units? (Wall resolved or > wall modeled?) > > And to confirm, are you doing a nonlinearly implicit velocity-pressure > solve? > > > I've found one-level DD to be ineffective when applied monolithically or > to the momentum block of a split, as it scales with the mesh size. > > I wouldn't put too much weight on "scaling with mesh size" per se. You > want an efficient solver for the coarsest mesh that delivers sufficient > accuracy in your flow regime. Constants matter. > > Refining the mesh while holding time steps constant changes the advective > CFL number as well as cell Peclet/cell Reynolds numbers. A meaningful > scaling study is to increase Reynolds number (e.g., by growing the domain) > while keeping mesh size matched in terms of plus units in the viscous > sublayer and Kolmogorov length in the outer boundary layer. That turns out > to not be a very automatic study to do, but it's what matters and you can > spend a lot of time chasing ghosts with naive scaling studies. >
