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January 11, 2019, 11:10 |
leastSquares vs. Gauss linear
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#1 |
Senior Member
Join Date: Jul 2013
Posts: 124
Rep Power: 13 |
Hi all,
Quick question: is there any general rule about when to pick leastSquares vs. Gauss linear for Grad(U)? From what I've read, it seems like leastSquares is more accurate when you have skewness in the mesh. Thanks! |
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January 11, 2019, 11:42 |
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#2 |
Senior Member
Anton Kidess
Join Date: May 2009
Location: Germany
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Rep Power: 30 |
Quick answer: Always use LSQ unless you run into troubles.
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*On twitter @akidTwit *Spend as much time formulating your questions as you expect people to spend on their answer. |
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January 11, 2019, 11:43 |
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#3 |
Senior Member
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Great, thanks so much!
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January 11, 2019, 14:59 |
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#4 |
Senior Member
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Posts: 124
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Hi, sorry one more question, does that also apply to Grad(p)?
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January 12, 2019, 09:24 |
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#5 |
Senior Member
Peter Baskovich
Join Date: Jul 2014
Posts: 127
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I've seen it recommend to use LSQ unless you're on a tet mesh because of osciillitatory behaviour. I've also seen it recommend to never apply limiters on p field and that p should use Gauss linear as it is not a convective term.
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January 14, 2019, 08:51 |
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#6 |
Senior Member
Anton Kidess
Join Date: May 2009
Location: Germany
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Why would it matter if the gradient you are evaluating is part of the convective term or not?
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*On twitter @akidTwit *Spend as much time formulating your questions as you expect people to spend on their answer. |
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January 14, 2019, 09:20 |
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#7 |
Senior Member
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Posts: 124
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@akidess: So do you always use leastSquares for both grad(U) and grad(P)? I had one experience recently where a low-Reynolds number solution converged with grad(p) Gauss linear but diverged with grad(p) leastSquares. I guess this is probably due to a poorly designed mesh?
Thanks! |
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January 14, 2019, 09:54 |
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#8 | |
Senior Member
Peter Baskovich
Join Date: Jul 2014
Posts: 127
Rep Power: 12 |
Quote:
gradient schemes |
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