Pistol Ammunition Ballistics Part 2
BY Herschel Smith6 years, 12 months ago
In Oversimplifying Ammunition Ballistics I had an argument with Tam, who is an NRA writer, and she doesn’t like the idea of “flying dimes.” Ridiculous, said I. And you can read the rest for yourself.
Today I passed through The Firearm Blog, and normally I like what I see there to some degree, including the comments, but this one just caused me to laugh.
They have a picture of a man (obtained via Facebook) who had a bullet lodged in his head, still visible. Must have been a squib load, must have been a reload, he must have been wearing a helmet, and on and on the comments go.
Pitiful .45 ACP, said a few. Shooter should have used something else like the much more effective 9mm. One commenter said that the .45 ACP penetrates farther than the 9mm, and so there must have been shielding in between the muzzle and his head (like a helmet). The response to this commenter was that he lost all respect because he said that the .45 ACP penetrates farther than the 9mm.
Good grief. So much chaos in one place is mind boggling. I don’t know how many readers actually dropped by the ballistics tests run by Lucky Gunner that I linked in my original post, but probably not many. I usually have readers for under two minutes, so blogging is something that must be done where readers can digest quickly.
But after I read those comments, I did a little bit of calculating on those test results for 9mm, .40 S&W and .45 ACP. Here is what I got for their self defense loads. I discarded the 2 (two) lowest penetration depths for all three rounds, as they appeared to be outlier data points.
9mm: Average penetration depth = 17.762 inches, standard deviation = 2.777, maximum penetration = 26.5 inches. This gives a fractional standard deviation (FSD) of 0.156 or 15.6%. Mass of bullet achieving maximum penetration = 124 gr.
.40 S&W: Average penetration depth = 19.034 inches, standard deviation = 5.637, maximum penetration = 32 inches. This gives a fractional standard deviation of 0.296, or 29.6%. Mass of bullet achieving maximum penetration = 180 gr.
.45 ACP: Average penetration depth = 18.867 inches, standard deviation = 5.009, maximum penetration = 31.2 inches. This gives a fractional standard deviation of 0.265, or 26.5%. Mass of bullet achieving maximum penetration = 200 gr.
Various bullet masses were used for the tests. This doesn’t give room for either (a) Tam to claim that lighter weight bullets are “flying dimes,” or (b) the commenter at TFB to claim that .45 ACP penetrates farther than 9mm (at least, not much farther). It also certainly doesn’t give room to tell that commenter that he has lost all respect of the firearms community. Such exaggeration is juvenile.
Here is the problem. An astute Monte Carlo analyst would tell you that these problems haven’t converged. Most analysts like to see on the order of 5% – 10% FSD before developing any confidence in the system. There may also be some issues with these rounds, in that there was inconsistent or incomplete expansion of every “maximum penetration” round for each of the three calibers.
More data is needed, and I didn’t run a VOV (variance of the variance) on these samples since the sample size is so small. The problem needs to converge before developing confidence in the system. The trouble is that this takes ammunition, ballistics gelatin, denim, test apparatus, and human resources. None of this is cheap.
There is also the issue of differing masses of bullets, but since the sample size is small for caliber, it’s even smaller for bullet mass within a caliber. But suffice it to say that lighter mass bullets aren’t flying dimes, and you can examine the data for yourself.
It’s also clear that each round performs well and penetrates far enough to do massive damage (except perhaps for the outlier data points). Ammunition brand is also a consideration.
The point of all of this is that if you want to make hyperbolic and exaggerated statements concerning much of anything, be my guest. I prefer to be a thinking man. And if Lucky Gunner wants assistance in analyzing the performance of any other tests, I’m available. But I do recommend proper convergence of the data sets. That requires more shooting.