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Old   September 18, 2009, 11:26
Default Small Y+
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Shannon Galway
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Is there a disadvantage to a small Y+? I know for shear stress transport models I am looking for a Y+ less than approximately 2. Is there a disadvantage/error to having this number much smaller than that (like 0.2 for example)?
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Old   September 25, 2009, 10:08
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federico
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Quote:
Originally Posted by sgalway View Post
Is there a disadvantage to a small Y+? I know for shear stress transport models I am looking for a Y+ less than approximately 2. Is there a disadvantage/error to having this number much smaller than that (like 0.2 for example)?
Are you simulating a wall-bounded turbulent flow? if you use DNS or LES your first computational node off the wall must be at y1+ = 1 or even y1+=0.5, but this mean a very large ammount of nodes. With wall function (this means that you are not making DNS anymore) you can put your first node in the log zone, so y1+ > 30, and you can save the number of computational nodes.
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Old   September 25, 2009, 14:43
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kumar
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Hi For wall integration grids we need to have y plus around 0.2 to 1. where as with the low y plus values you will see some convergence issues. With the low y plus values there is possibility to predict wrong gradients. That will screw up your complete solution.
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Old   September 25, 2009, 23:23
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Shannon Galway
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Originally Posted by aatman View Post
Are you simulating a wall-bounded turbulent flow? if you use DNS or LES your first computational node off the wall must be at y1+ = 1 or even y1+=0.5, but this mean a very large ammount of nodes. With wall function (this means that you are not making DNS anymore) you can put your first node in the log zone, so y1+ > 30, and you can save the number of computational nodes.
I am modeling the leg of an offshore jackup drilling rig. Therefore, this is an open flow around an obstruction.

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Originally Posted by cfd_lean View Post
Hi For wall integration grids we need to have y plus around 0.2 to 1. where as with the low y plus values you will see some convergence issues. With the low y plus values there is possibility to predict wrong gradients. That will screw up your complete solution.
Can you expand on the "convergence issues". Why would low Y+ values give convergence problems?

Thanks for all the help. I really appreciate it.
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