Ok, I was sitting arount the house this afternoon and generally crying on my paws over the windy weather and a nasty chest cold I picked up over the weekend and I got to wondering. . .
I was wondering about what I'll call the "Dream Table" for my canopy. Right now, I'm mostly jumping a Mojo 280. The table I'd like to see would include the following dimensions:
Independent variables
1. Delay, i.e. feet from exit until pilot chute deployment;
2. Pilot chute size and design (vented versus non-vented);
3. Packing configuration (slider up, slider down, indirect/direct line control techniques);
Dependent variable
4. Distance, in feet, the pack job requires from PC deployment until a pressurized, flying canopy wing is present.
4a. Standard deviation/variance of variable 4, as a proxy measurement for how consistent the opening is in terms of vertical distance required.
Why is this the Dream Table? Well, it would allow one to calculate exactly how much delay could be taken for any given gear configuration (on a given canopy) and delay, and thus take the guesswork out of deciding when to dump. Of course, you can always dump high and be "safe" but there are many jumps out there where a lower deployment is safer so long as it isn't too low in terms of canopy pressurization.
The other interesting thing about the Dream Table for a given canopy is that I bet 10 different jumpers would give 10 different estimates of what the numbers would be in the DT. I've had several conversations where experienced jumpers had pretty different answers to questions like "how many feet does a vented canopy chew up on a slider up deployment with 38 inch pilot chute and a 3.5 second delay?" Of course one must hold wing loading constant, and make an assumption that the PC is properly folded and deployed. It is trivially easy to make a major PC hesitation with a funky PC pack job or crappy deployment (I've tested this myself of course).
So, does the above deployment take 100 feet, 150 feet, 200 feet? What is the variance/standard deviation?
The DT could be developed, at least for sub-termimal ranges, with alot of controlled jumps from an object like the Perrine. I'm estimating there'd be many dozens of jumps needed to fill the table in completely, and it'd take alot more to add statistical significance to the variance estimates. Still, if someone did this (like a gear manufacturer?), it would clear up an area of major uncertainty in BASE.
I think that, practically speaking, jumpers with hundreds of jumps have a rough estimate of the DT in their heads and call on it when jumping, but I've never seen even these estimates written out. To do so would require weighting estimates for each variable, and it's not clear that most of these interactions would be linear.
For instance, how much more feet does a slider down deployment take on a 2 second delay with 42 inch PC versus a 46 inch PC (both non-vented). From my own subjective experience, I'd say about 30-40 feet more. But is that really accurate?
Or, how many more feet does a deployment take with a 42 inch PC and a 1.5 second delay versus a 3 second delay? Are they the same number of feet (about), but the deeper delay means faster rate of fall makes the canopy extraction and pressurization seem "faster" even though the same amount of vertical fall distance is required? Or does the deeper delay really take up less vertical feet on opening, ceteris paribus?
Finally, with these raw data one could do all sorts of interesting graphical representations of the data set. This could point out anomalies, where for example a LONGER delay might eat up less vertical feet than a shorter delay with certain PC sizes on certain canopies.
Another example: you find yourself at the top of a 350 foot tower, packed slider down. For some odd reason, you have only a 38 inch pilot chute with you. The landing is gnarly and you want a canopy over your head with as much height above the ground as possible. A static line won't work because the winds are wrong. Do you go-and-throw? Do you take 2.5 and build up some airspeed? Something in between? Does it all cosmically balance out and no matter what you get about the same result?
Has anyone ever done systemic analysis of opening performance at different delays with different PCs? If so, would they be willing to share those data?
Peace,
D-d0g
ddog@wrinko.com
www.wrinko.com




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