1. ADR Data Acquisition – From Download to Meaningful Data
We find a lot of people think accident data presentation is a one button process.
It’s not
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2. Example – It’s not always what it looks like
Personnel
Process at the track
Tools used
Example – It’s not always what it looks like
Data overlaid on video example
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3. Indy Car Accident Investigation
Personnel
One full time (Me)
One permanent part time
One rotating (per race) part time
One consultant (Trammell)
Jobs Performed at track
Safety inspection on tech day (Helmets, Ear sensors, and Cars)
Crash Box Download
Pictures of crashed cars
Database entry
2012 – 2015 (New Car)
Average 70 Impacts investigated per Year
Pool of 10 people to pick that rotating person from. Most are Engineers
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4. Tools Used for Analysis
For graphing we use National Instruments - Diadem
(Same program as Vandalia and CAPE use)
For video photo analysis we currently use Adobe Premier Elements and Adobe Photoshop.
(We often use VLC media player for playback)
Pi Toolbox is used for chassis/engine data analysis
Our crash box spits out Diadem files for direct import
I’ve written custom script files for filtering and graph production
Using diadem allows me to import files from our sled test into the same environment so I can do custom graphs from sled test for analysis
New crash box will be excel based files, we will still use Diadem for our analysis
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5. Data Collection Process
For Indy Car and Indy Lights only cars that come in on a wrecker are downloaded
- To much damage to continue
All cars are brought back to the garage area
Once I see a car I can usually have crash data uploaded to our website within 5-10 minutes
- Current system requires physical plug into car
We also collect:
- Videos from our Race Control system
- Videos from the internet (if necessary)
- Photos of crashed car
- Track Photos (if necessary)
Often make team shop visits to look at cars after they are torn down
Consultation with Doctors (Trammell)
Consultation with Safety Team (M Yates)
Bone yard no longer used
We don’t have the infrastructure to do successful wireless downloads
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6. Example Analysis
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7. Target Car
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8. Example of Rough Track Data
Example from a rough street course race
This is why airbags would struggle to work in one of our cars
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9. Target Car
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10. Target Car
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11. Target Car
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12. Target Car .150 seconds Final output 1000 Hz Data
Filtered with CFC 60 Filter
Channel Frequency Class
3 db limit freq 100 Hz
Stop damping -30 dB
Sample freq > 600Hz
We picked filter because that’s what the crash sleds were using
.150 seconds
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13. Data Output from Crash Box Download
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14. Target Car 60.7 G’s Lateral Example
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15. Bullet Car Nose Input pulse was provided by nose of bullet car
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16. Bullet Car
Bullet car didn’t show similar G’s in the Longitudinal plane
Need to look at resultants
25 G’s Longitudinal
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17. Bullet Car
Bullet car didn’t show similar G’s in the Longitudinal plane
Contribution of Lateral Component ?
Need to look at resultants
25 G’s Longitudinal
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18. Bullet Car
Even Bullet car resultants were not on the same order as the Target car
All Peaks less than the
60.7 G’s Seen on Target car
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19. Target Car
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20. Bullet Car vs Target Car
Target car Lateral G’s
Bullet car Longitudinal G’s
(Inverted)
Bullet car Longitudinal G’s vs Target car Lateral G’s
When you overlay Target car Lateral G’s with Bullet car Longitudinal G’s the 60 G spike is unaccounted for. Even if you look Bullet car resultant G’s on the previous page they are still below 30 G’s at the same point as Target cars 60 G spike.
Lower level of Bullet car G’s a result of only looking at single axis and not using the resultants
** Bullet car Longitudinal G’s are inverted for graph clarity
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21. Bullet Car vs Target Car
Crack in floor extends
under crash box
Crash Box location
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22. Target Car Speed From Video
Target car’s speed just before impact with Bullet was calculated using distance on the track vs. time as calculated and observed from the video.
The portion of the slide used covered 6 poles and 54 video frames.
Fontana has not responded back on pole placement, it was observed from Google maps that they were 18 foot apart.
Using this information Target car skidded 108 feet in 1.8 seconds for an average speed of 40.9 mph
If 20 foot pole spacing is used then speed goes to mph
** The next slide is screen shots from video used for above calculations.
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23. Bullet Car vs Target Car1 2 3 4
The struggle in calculations like this is with the slow video rates
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24. Target Car Speed Calculation
Speed when front wheel starts spinning again as observed from video, is when Target car and Bullet car separates
Speed at this point is 101 mph
Delta V, = 40 mph over time of contact
Because of the nature of this accident we were able to validate the Delta V calculation.
The Pi data shows us the beginning of contact and the separation of the two cars
The math show a 40 mph delta V
Bullet
Negative Longitudinal G spike
Indicates hit with Target car
Speed at this point 142 mph
Bullet
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25. Bullet Car Delta V From Crash Box
Calculated Delta V approx. 38 mph
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26. Target Car Delta V From Crash Box
3 axis approx. 56 mph
2 axis (X,Y) approx. 51 mph
Higher Delta V for Target car is probably a result of Bullet car “punting” it forward from impact
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27. James Jakes Data Over Video
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