I hereby nominate Hitech for the "most diligent information gatherer of the year" award. How in the world did you find those two .pdf reports? I gave up a couple of weeks ago after no luck in finding anything concerning lateral forces on spheres. I am impressed! 
I would give the coefficient (Cs) an average value of around 0.06, judging from figure 1 in the file AIAA_Apr_2002.pdf.
To determine what this means, you need to plug that coefficient into a drag-like force equation; here ya go:
Fs = 0.5 * rho * V^2 * Cs * A, where
Fs is the side force experienced by the paintball,
rho is the density of the air (around 1.239 kg/m^3),
V is the velocity of the air relative to the paintball (around 85.3 m/s for a 280 fps shot),
Cs is the side force coefficient (around 0.06), and
A is the cross sectional area of the paintball (around 0.000234 m^2).
Plug in the numbers, stir gently, and you get a side force of around 0.063 newtons.
What does this mean? Well, let's see what we get for a lateral acceleration resulting from this side force. F = m * a is all we need. The mass of a paintball is around 0.003 kg.
a = F/m
a = 0.063 / 0.003 = 21.1 m/s^2
21 meters per second squared for a lateral acceleration... that's over 2 g's of sideways acceleration this thing is experiencing, and that's for only one shed vortex. There are a couple/few hundred shed vortices during the flight of a paintball. About the only thing that helps us get some level of accuracy out of a paintball is that those vortices seem to be shed in random orientations.
If I get a chance this weekend, I'll see what I can do about generating a random walk using this type of data. The walk will be a random direction walk using random step sizes. We can then plug the results of that walk into a motion model to see where the paintball should fall. Rinse/repeat several times and you end up with a distribution function describing where a paintball will likely strike relative to its aim point.
BJJB

Originally posted by hitech
It appears that the side drag coefficients for a sphere are only an order smaller magnitude than the "forward" drag coefficient. While I will have to determine what that really means, I believe THAT IS A HUGE FORCE. If that is true it is amazing that a paintball ever hit anywhere near where it is aimed.
Added on edit: If I am reading correctly the side coefficient is 0.1.
It appears that the side drag coefficients for a sphere are only an order smaller magnitude than the "forward" drag coefficient. While I will have to determine what that really means, I believe THAT IS A HUGE FORCE. If that is true it is amazing that a paintball ever hit anywhere near where it is aimed.
Added on edit: If I am reading correctly the side coefficient is 0.1.
To determine what this means, you need to plug that coefficient into a drag-like force equation; here ya go:
Fs = 0.5 * rho * V^2 * Cs * A, where
Fs is the side force experienced by the paintball,
rho is the density of the air (around 1.239 kg/m^3),
V is the velocity of the air relative to the paintball (around 85.3 m/s for a 280 fps shot),
Cs is the side force coefficient (around 0.06), and
A is the cross sectional area of the paintball (around 0.000234 m^2).
Plug in the numbers, stir gently, and you get a side force of around 0.063 newtons.
What does this mean? Well, let's see what we get for a lateral acceleration resulting from this side force. F = m * a is all we need. The mass of a paintball is around 0.003 kg.
a = F/m
a = 0.063 / 0.003 = 21.1 m/s^2
21 meters per second squared for a lateral acceleration... that's over 2 g's of sideways acceleration this thing is experiencing, and that's for only one shed vortex. There are a couple/few hundred shed vortices during the flight of a paintball. About the only thing that helps us get some level of accuracy out of a paintball is that those vortices seem to be shed in random orientations.
If I get a chance this weekend, I'll see what I can do about generating a random walk using this type of data. The walk will be a random direction walk using random step sizes. We can then plug the results of that walk into a motion model to see where the paintball should fall. Rinse/repeat several times and you end up with a distribution function describing where a paintball will likely strike relative to its aim point.
BJJB






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