Small Y+

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 September 18, 2009, 10:26 Small Y+ #1 New Member   Shannon Galway Join Date: Sep 2009 Posts: 4 Rep Power: 10 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)?

September 25, 2009, 09:08
#2
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federico
Join Date: Aug 2009
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Quote:
 Originally Posted by sgalway 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.

 September 25, 2009, 13:43 #3 New Member   kumar Join Date: Sep 2009 Posts: 4 Rep Power: 10 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.

September 25, 2009, 22:23
#4
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Shannon Galway
Join Date: Sep 2009
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Quote:
 Originally Posted by aatman 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.

Quote:
 Originally Posted by cfd_lean 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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