Tuner Testing Results
Tuner Testing Example
For those that don’t feel like reading the entire article the first few bullets are the cliffs notes
- A rifle fixture was used to eliminate all potential shooter error
- Approximately 140 rounds were fired for the test using a 223 and bulk ammo
- The best node identified produced a 72% improvement over the worst node during initial tuning
- Even with bulk ammo with a 50fps ES, there was an approximate 20% improvement in performance with the tuned node over a 5x5 aggregate sample size.
- Results can be expected to improve even more by using more consistent ammo. Ammo consistency is defined as ammo with more consistent seating depths and charge weights to maintain lower ES/SD.
When it comes to setting up a testing platforms and test cases for evaluating shooting applications such as ammo quality, or the impacts of additional devices, you have to consider all sources of error or noise that can contribute to potentially misleading data. Additionally, you have to take into consideration the inherent precision of the platform and evaluate how potential sources of error may impact your ability to determine a valid result vs potential error. A good example for how to think about his would be as follows:
If you have a rifle platform that is shooting 1MOA (1” @100 yards) and you’re attempting to determine if you can improve that performance by 25%, that means that the combination of your equipment, shooting method and sources of error must be more capable of performing within the range of potential improvement or else you will not be able to determine any statistical difference in group sizes. (i.e. The testing setup must be capable of consistently performing better than the .25” over an appropriate sample size.
What are potential sources of error
- Shooter capability and repeatability with repeatability being key.
- Environmental conditions
- How a shooter responds to environmental conditions such as image quality when adjusting between shots. Depending on the time of year, number of shots fired during the testing, etc. you will be impacted by mirage from the barrel or external environmental conditions downrange. A shooter making adjustments during the firing cycle is introducing potential error as assumptions for corrections are made by the shooter and adjustments are made to the Point of Aim (POA) to adjust based on what the shooter sees through the optic. Using rifle fixtures that maintain a consistent return to zero without a shooter’s involvement help minimize these situations. We have all seen aiming points “move and dance” when there is mirage present or as a barrel warms with repeated shot strings.
- Inherent precision of the rifle
- Inherent precision of the ammo
Selecting the right platform and eliminating variables.
As the inherent precision of the platform (rifle/ammo) improves, the ability to identify the magnitude of the change related to modifications to the system such as tuner adjustments becomes more difficult. As a result it becomes critical to look at the system as a whole and adjust the testing scenarios and platforms accordingly. More broadly speaking, when the differences in the results are closer to each other, any source of error impacts the ability to determine improvements from the resulting test data and testing platforms used need improved accordingly.
Example:
- If I make a 25% improvement to a rifle that the inherent precision is 1.25MOA or 1.25” groups at 100 yards, that improvement is equal to a reduction in group size of .3125”
- If I make a 25% improvement to a rifle that the inherent precision is .5MOA or .5” groups at 100 yards, that improvement is equal to a reduction in group size of .125”
- If I make a 25% improvement to a rifle that the inherent precision is .25MOA or .25” groups at 100 yards, that improvement is equal to a reduction in group size of .0625”
- With a .5 MOA rifle a 25% improvement could be completely hidden on paper with a flawed test setup where sources of error introduced are greater in magnitude than the improvement.
The same scenario and results have been shown below at further distances.
|
Distance in Yards |
||||||
|
100 |
300 |
500 |
600 |
800 |
1000 |
|
|
Group Size at distance with 1MOA Rifle |
1 |
3 |
5 |
6 |
8 |
10 |
|
Group Size at distance with 1MOA rifle with 25% improvement |
0.75 |
2.25 |
3.75 |
4.5 |
6 |
7.5 |
Actual Testing Results
The below test was performed with a 223 bolt action rifle using the equivalent of mass produced bulk ammo. This ammo was loaded on a Dillon 1050 with an Autodrive using ball powder. This is training ammo for positional shooting use and we have seen 50fps velocity swings so while its not an ideal ammo to show potential consistent improvements that are achievable with a tuner, it does allow us to quickly see if we can determine a measurable difference using just the tuner. In order to remove as many sources of error as possible this rifle was shot using a Young Railgun setup that had been modified to allow us to clip a rifle into the platform using the existing ARCA rail on the chassis. Aiming points and tune settings were adjusted between groups and then the Rail Gun was used to shoot all shots without any shooter inputs other than touching the trigger.
Testing Setup
Ammo: Bulk loaded using Dillon 1050 with Autodrive, CFE 223 and 75gn amax (ES ~50fps)
Rifle: 1:7.5 Twist barrel 223 chamber, Bighorn TL2 Action
Rifle Fixture: Young Rail Gun modified to allow for attaching an entire rifle directly to the top plate interface via an ARCA rail and ARCA clamp.
Video overview of test setup and usage
Testing Approach
We followed the ATS tuning instructions however used 3 shot groups for the initial tune test in order to present a larger sample size for data analysis as well as went well beyond the initial identified nodes to gather data across a larger range of settings. Between groups, the tuner was adjusted 2 hashes as defined in the instructions. Groups were shot from Left to Right, from Bottom to Top in the pictures provided below.
After approximately 2.5 full revolutions, we selected what we felt was the best node and the worst node and then proceeded to shoot a 5x5 aggregate for each of those settings and then analyzed the results. (Note: The node identified as the best was found within 20 shots as suggested within the instructions.)
Results have been provided below and the entire set of groups and target have been included for reference. Approximately 140 shots were fired in this evaluation between rifle zero and testing. Group sizes were measured using the Range Buddy application.
|
|
Size Data for .224 cal bullet groups initial Tuner Settings |
|||
|
Node |
Width in Inches |
Height in Inches |
Group Size in inches |
Group size in MOA |
|
|
|
|
|
|
|
Bad Node |
0.67 |
1.1 |
1.17 |
1.12 |
|
Good Node |
0.16 |
0.28 |
0.33 |
0.31 |
|
|
% Difference of Good Tune setting vs Bad |
72.3% |
||
|
|
Size Data for .224 cal bullet groups 5x5 Aggregate for worst vs best tuner settings |
|||
|
BAD Node / Group |
Width in Inches |
Height in Inches |
Group Size in inches |
Group size in MOA |
|
1 |
0.56 |
0.69 |
0.86 |
0.82 |
|
2 |
1.05 |
0.55 |
1.06 |
1.02 |
|
3 |
0.49 |
0.38 |
0.61 |
0.58 |
|
4 |
0.27 |
0.92 |
0.92 |
0.88 |
|
5 |
0.33 |
1.33 |
1.35 |
1.29 |
|
Averages |
0.5925 |
0.635 |
0.8625 |
0.825 |
|
|
Size Data for .224 cal bullet groups 5x5 Aggregate for worst vs best tuner settings |
|||
|
GOOD Node / Group |
Width in Inches |
Height in Inches |
Group Size in inches |
Group size in MOA |
|
1 |
0.47 |
0.33 |
0.49 |
0.46 |
|
2 |
0.34 |
0.23 |
0.36 |
0.34 |
|
3 |
0.63 |
0.49 |
0.74 |
0.7 |
|
4 |
0.89 |
0.69 |
1.06 |
1.02 |
|
5 |
0.85 |
0.55 |
0.91 |
0.87 |
|
Averages |
0.636 |
0.458 |
0.712 |
0.678 |
|
|
|
|
|
|
|
% Improvement of Good Tune setting vs Bad in 5x5 aggregate |
17.4% |
17.8% |
||
Conclusions
- A rifle fixture was used to eliminate all potential shooter error
- Approximately 140 rounds were fired for the test using a 223 and bulk ammo
- The best node identified produced a 72% improvement over the worst node during initial tuning
- Even with bulk ammo with a 50fps ES, there was an approximate 20% improvement in performance with the tuned node over a 5x5 aggregate sample size.
- Results can be expected to improve even more by using more consistent ammo. Ammo consistency is defined as ammo with more consistent seating depths and charge weights to maintain lower ES/SD.
Full target including all groups and markup of identified best/worst node and 5x5 aggregate testing for each
Best Node Selected for Testing
Worst Node Selected for Testing
Groups are shown left to right as shot and can be referenced to the comprehensive target to validate.
5x5 groups for “Best” Node testing
5x5 groups for “Worst” Node testing
