Compare Polars

Was just thinking it would be fun if there was a website (or software) that you could overlap polars of multiple gliders at the same time to compare them? Does this exist?

Thanks!
WC

There is a spreadsheet that allows comparison of quite a few polars he https://www.gliding.com.au/assets/docs/Polar10.xls

On Friday, December 22, 2017 at 11:28:11 AM UTC-5, Tony wrote:
There is a spreadsheet that allows comparison of quite a few polars he https://www.gliding.com.au/assets/docs/Polar10.xls

Thanks Tony, I'll have some fun playing with this!

-WC

On Friday, December 22, 2017 at 8:28:11 AM UTC-8, Tony wrote:
There is a spreadsheet that allows comparison of quite a few polars he https://www.gliding.com.au/assets/docs/Polar10.xls

It is a really good ap....too bad it is not up to date and does not include some of the newer models.

On Friday, December 22, 2017 at 11:28:11 AM UTC-5, Tony wrote:
There is a spreadsheet that allows comparison of quite a few polars he https://www.gliding.com.au/assets/docs/Polar10.xls

This is interesting data to me, but I open it up, and look at the "gliders" table of the raw data, and I cannot make any sense of what I am seeing.

What is "G/F" ... and then after that looking across the table, look at the first line, for an ADSH-25e ... yes, pretty high-performance sailplane ... but it says the units are "mps" (surely meters per second ?) ... but then the first entry is of 80? 80 what? 80 m/s ... yowsa, that's ≈ 160 kts!

and at "80" the value in the table is is 0.62 ... what is that? If that were the sink speed in m/s then the L/D would be 80/0.62 = 129 ... no way! So what are the numbers?

Can somebody explain WTF I am looking at here?

At this point I should mention that I really have been looking for these data. and I am an applied mathematician/scientist by trade and have been studying risk tradeoff optimization in speed-to-fly problems, this is also basically the same problem as optimal handicapping in disguise.

Is there interest in discussion of these issues? I could point out some issues where the current methods aren't entirely right or complete, that do have pretty straightforward solutions.

One other point I would make ... for all calculational purposes, you want to reduce the polef data to a fitted function of some sort, and boy ... are polynomials convenient for this purpose in this case. The standard "McCready Speed to Fly" just assumes the polar from best L/D on up is fitted with a quadratic, after trivial calculus and a little algebra the speed-to-fly is computed by solving the quadratic equation. This is easy to generalize to better fits.

And when you see this, and go through just a little math, what you see you want for the polar are stated minimum sink and best-L/D speeds & sinks, and then at least one, preferably 2 or 3 data-points at higher speeds ... and you don't need anything more than that.

The reason minimum sink and best-L/D are so important to defining the polar should be intuitively obvious, but there's a mathematical reason too ... these provide additional important equation constraints on the fitted function

minimum sink is of course s'(h) = 0

best L/D means that s(h) = h / s'(h)

where h is the horizontal speed (that what's really the independent variable in a polar, NOT airspeed, although at the very high L/Ds of gliders the differences between these two is negligible) s(h) is the sink rate at horizontal speed h, and ' means first derivative.

Forth these two "special" points you get two constraint equations, not one. Playing around with real polar data it takes a 5 to 6 order polynomial to really fit one well, and for manipulating all the ensuing calculations it is the coefficients of that polynomial that is wanted.

Also, I don't see listed gross weights for these test data? That is important ... to do ballast corrections etc.

The help page seems clear enough

Cell H21 says 80 is the speed in kph at which the sink rate is measured.
Cell F19 says .62 is the sink rate in mps

The glider weight is included in the wing loading column.

I don't have much interest in discussing failings in these calculations because I'm pretty happy to have the spreadsheet as it is.

OTOH, if you have energy to put more gliders into the data set, that would be interesting.

ok, I'm not getting the "cell says", perhaps not so up on xls spreadsheets etc. I am working with the CSV exported data...

what is the "wing loading column?" Is that G/F? What units?

what are the units for the rows where the units are specified as "kts?" Are the airspeeds all in kph for all rows, sink rates in mps or kts as stated?

Ok, the .csv thing explains your problem.

The .xls file is not just a spread sheet, but rather a workbook of sheets that work with Excel.

Without that, I can see your frustration and can offer no help.

You are kind of in a dark hole of your own digging.
Suggest you stop digging and find a copy of Excel.

I'm pretty sure there is no value in fitting a 6th order polynomial. The data isn't that good.

On Friday, December 22, 2017 at 12:22:05 PM UTC-8, wrote:
On Friday, December 22, 2017 at 11:28:11 AM UTC-5, Tony wrote:
There is a spreadsheet that allows comparison of quite a few polars he https://www.gliding.com.au/assets/docs/Polar10.xls

This is interesting data to me, but I open it up, and look at the "gliders" table of the raw data, and I cannot make any sense of what I am seeing.

What is "G/F" ... and then after that looking across the table, look at the first line, for an ADSH-25e ... yes, pretty high-performance sailplane .... but it says the units are "mps" (surely meters per second ?) ... but then the first entry is of 80? 80 what? 80 m/s ... yowsa, that's ≈ 160 kts!

and at "80" the value in the table is is 0.62 ... what is that? If that were the sink speed in m/s then the L/D would be 80/0.62 = 129 ... no way! So what are the numbers?

Can somebody explain WTF I am looking at here?

At this point I should mention that I really have been looking for these data. and I am an applied mathematician/scientist by trade and have been studying risk tradeoff optimization in speed-to-fly problems, this is also basically the same problem as optimal handicapping in disguise.

Is there interest in discussion of these issues? I could point out some issues where the current methods aren't entirely right or complete, that do have pretty straightforward solutions.

One other point I would make ... for all calculational purposes, you want to reduce the polef data to a fitted function of some sort, and boy ... are polynomials convenient for this purpose in this case. The standard "McCready Speed to Fly" just assumes the polar from best L/D on up is fitted with a quadratic, after trivial calculus and a little algebra the speed-to-fly is computed by solving the quadratic equation. This is easy to generalize to better fits.

And when you see this, and go through just a little math, what you see you want for the polar are stated minimum sink and best-L/D speeds & sinks, and then at least one, preferably 2 or 3 data-points at higher speeds ... and you don't need anything more than that.

The reason minimum sink and best-L/D are so important to defining the polar should be intuitively obvious, but there's a mathematical reason too ... these provide additional important equation constraints on the fitted function

minimum sink is of course s'(h) = 0

best L/D means that s(h) = h / s'(h)

where h is the horizontal speed (that what's really the independent variable in a polar, NOT airspeed, although at the very high L/Ds of gliders the differences between these two is negligible) s(h) is the sink rate at horizontal speed h, and ' means first derivative.

Forth these two "special" points you get two constraint equations, not one. Playing around with real polar data it takes a 5 to 6 order polynomial to really fit one well, and for manipulating all the ensuing calculations it is the coefficients of that polynomial that is wanted.

Also, I don't see listed gross weights for these test data? That is important ... to do ballast corrections etc.

I'd appreciate it if somebody would answer "what is G/F" ... is that the wing loading and if so in what units?

As to all of this dealing with ms-format xls spreadsheets ... if it's your tool of choice, fine ... but it's not mine, and I just wanted the data out, and other than the issue of the gross weight or wing-loading ... I've got that done.

I would make the following points however, as a working scientist/engineer:

* you'll find (if you look) that journal standards for "supplementary material" and funding-agency data retention requirements (NSF, NIH, DOE, NASA) ban, at least strongly discourage, proprietary or spreadsheet data formats, in favor of ascii-delimited, or NetCDF

* "can't help you there" ... is not accepted

On Saturday, December 23, 2017 at 11:44:41 AM UTC-5, jfitch wrote:
I'm pretty sure there is no value in fitting a 6th order polynomial. The data isn't that good.


Ah, now this is a more interesting issue, that has several aspects. Some things to think about:

* for almost every test, the minimum sink speed and the best L/D points are given, and in some cases this is all the data for which you get actual numbers without digging, or trying to digitize data from squinchy graphs etc.

* It is important for general application that the fit get the minimum sink and best-L/D right. If you don't believe me on this point, we could discuss further. But you'll find that you cannot get a polynomial that does these right AND gets the higher-speed data right ... without 5 or 6 terms. Go away and give it a try..

The fundamental reason for all of this is that the drag is reasonably described as the sum of drag terms, with the dominant terms are the induced drag and the "profile drag."

The induced drag is proportional to the lift-coefficient squared, and when you grind that out it falls as 1/v ... and polynomials don't fit that well with few terms ... that's the real reason you need more.

This leads to the following point/idea ... nothing magical a about a polynomial, and if you want something with few terms that fits a polar pretty well and has a "reasonable" basis" consider (Ax + 1) ( B/x + C * x^2) ... easy to derive the standard best-glide and speed-to-fly equations with this. (and A is generally small)

Related to the above issues is "yes, the data aren't that good" in many cases, but OK, we know physics (aerodynamics) and our job isn't just to get "some line" through the data, our job is to get the best physically plausible estimate of the polar, from the data we have. Another reason for this is that often the data don't extend to higher speed ranges, etc.

Now this leads to one of the things that I am playing with to deal with these data, that consists of doing a drag fit to a model that includes terms for induced drag (including the epsilon term), a wing washout term vs AOA, using the airfoil drag-bucket curve if known (or a generic one if not), and a simple fuselage profile drag vs AOA function.

This yields a physically-realistic polar, given the physics we know (gets to be a much bigger nuisance for flapped sailplanes though, without getting handbook data and applying those) , and in principle allows us to "fix" not so good data to a a degree. It's also the most physically-plausible way to extrapolate the data to higher airspeeds if you need to, though doing is is always a reach.

The resulting system is something of a mess that one doesn't want to use as the function for speed-to-fly etc (it's messy and derivatives are messier), so it is easier to fit the result with a 5 or 6 term polynomial for subsequent use ... and this is just another way of saying what I have said above -- takes a polynomial with a fair number of terms to approximate a real drag model, because the physics has that pesky induced drag term, and some sort of drag-bucket approximation.