Interesting project. About the lag in the framerate: would it help if you could download the file from YouTube to a local .mp4 file, so you can play it without interference from Youtube's servers and your internet link? Or are you already doing that and is the source material compromised?
Yes Semmel I can do that easily, it is the same effort for me.Do you expect ( 1 file for raw data + 1 file for filtred data) * each flight ? It will be a lot of files...
Very cool, Space Opera!Does SpaceX use the same reference frame all the way from take-off to orbit? My recollection from LEO launches was that the burn-out speed was consistent with circular speed in an inertial frame, but the that speeds early in flight were obviously in a rotating, Earth-fixed frame (otherwise the speed at lift-off would be over 300 m/s).Is the speed deduced at the moment the rocket reaches Mach 1 (I haven't seen recent launches, but in earlier launches this was called out) consistent with a rotating frame, allowing for a lag?
The raw data says they only ever reach 7480.6 m/s so I assume they -only- use inertial frame. As a 160km altitude orbit is 7811 m/s. Net: about the rotational speed they get for free.
Does anyone could provide the launch azimuth for each flight ? From this information, I should be able to reconstruct a crude 3D trajectory as well...
Quote from: S.Paulissen on 08/23/2016 11:22 pmThe raw data says they only ever reach 7480.6 m/s so I assume they -only- use inertial frame. As a 160km altitude orbit is 7811 m/s. Net: about the rotational speed they get for free.Thanks, S. Paulissen. I presume you mean "rotating frame" rather than "inertial frame."
That's awesome Semmel. I, too, caught the second stage throttle in your previous graph you made but did not comment on it. Your new graph is clearly superior as I did not notice the fairing separation at all. Great work!When I saw the acceleration curves the other day, it made me wonder if we could suss out a more definite mass of the fairing and second stage based on the change of acceleration from staging events.
C_0 = 0.07 # drag constant value at speed far below mach1
The most probable is that our numbers are wrong, but is it possible that the throttle is decrease before MaxQ ?
Quote from: Space Opera on 08/28/2016 01:45 pmThe most probable is that our numbers are wrong, but is it possible that the throttle is decrease before MaxQ ? I think they may actually be throttling down for the supersonic/transonic regime buffeting. John Insprucker sort of hinted at that in a few webcasts, IIRC. If you compare to the velocity plot, it seems to be around Mach 1.
This is awesome work. Are you writing the code in Python? What graphing package are you using?You might try checking your atmosphere against the NASA standard atmosphere of 1976. You can test individual points with this online calculator, or you can just use the model here.
Drag coefficient for an ogive-shaped fairing and long cylinder should be pretty easy to find in some basic aerodynamic texts and/or AIAA papers. This may not allow for easy internet research, but that kind of thing has been methodically studied by NACA/NASA since at least the 1930's.
My own MaxQ calculation show roughly similar results.The most probable is that our numbers are wrong, but is it possible that the throttle decreases before MaxQ ? Because clearly my curves show that the loss of acceleration seconds before MaxQ leads to a significant lower MaxQ than if the throttle was keep constant.
Quite possible. Actually an interesting proposal. I added the region of mach 0.9 to 1.2 to the plot. Not an exact fit but quite close. Interesting interesting interesting.
Quote from: Semmel on 08/28/2016 07:48 pmQuite possible. Actually an interesting proposal. I added the region of mach 0.9 to 1.2 to the plot. Not an exact fit but quite close. Interesting interesting interesting.Does that take into account the lower speed of sound at that altitude (10-ish km)? I think Mach 1 might be around 300 m/s or thereabouts there.
# air pressure depending on hightp = p_0 * np.exp(- g * M * h / (R * T_0))# air density depending on pressure and temperaturerho = p * M / (R * T)
The Saturn 5 is nice and all, but it has rather awkward shape and it had fins at the base, which increase Cd quite a lot.
I took this equation since its a bit simpler:https://en.wikipedia.org/wiki/Atmospheric_pressure#Altitude_variationYou find this equation not only on wikipedia, also many other sites use that form. I dont think the approximation can be responsible for the differences we see. It wouldnt be a well accepted one if that was the case.
First and foremost, fantastic work Space Opera!! I have indeed been harvesting data from the webcasts manually. Data from your automated tool will be a very useful contribution to those of us that like to plot/analyze flight data.Next, let me jump into the discussion about Semmel's plots (which are great!).1) Being able to see the fairing jettison event in the acceleration data is very cool! I just checked the webcast, and fairing jettison occurs at ~3:40 (220 s), which is a rather good match to what we're seeing!2) I'm with ugordan on the reason the first stage throttling down around the 50 s mark: I think it's for the transonic region before Mach 1. In my estimation, Mach 1 is passed at 62 seconds (there's no "going supersonic" callout in the webcast for this launch, sadly), so the throttling is definitely occurring prior to going supersonic, and well before max Q.3) As for the dynamic pressure issue, I redid Semmel's plots except that I'm using the ISA1976 standard atmosphere for density/temperature calculation (I have a Python implementation of it, which I'll gladly share if anyone wants it). I'm attaching a plot that compares my dynamic pressure, temperature and density curves to Semmel's for the first 185 seconds. Semmel's curves, which I reproduced from the code he pasted upthread, are shown as dashed lines (the temperature curves are nearly identical).Semmel: I think there's a typo in your temperature table. The bold value should be 228.65 (=-44.5°C):std_atm_T = [288.15, 216.65, 216.65, 288.65, 270.65, 270.65, 214.65, 214.65]It doesn't make a huge difference, though (and none whatsoever before the ~95 s mark); the attached plot uses the corrected value.We're using the exact same data for velocity and altitude, so the only difference is in the density calculation. Comparing the plots, it seems that the small difference we have in computed density is enough to noticeably alter our dynamic pressure curves. In my calculation, max Q occurs at 72.2 s, reaching a substantially lower value of 29.6 kPa, mainly because density falls off quicker in the ISA1976 model.Semmel's atmospheric model is a bit weird because he's assuming piecewise linearly-varying temperature yet uses the exponential formula for pressure (which is the solution for constant temperature). IntoTheVoid provided the correct formula in the case of linearly-varying temperature (and that's all the ISA1976 does, really).Still, Semmel's time of max Q is much closer to the callout in the webcast (which occurs at ~83 s) than mine, so I don't really know which to trust more. I think the bottomline is that the dynamic pressure curve is kind of sensitive to small details in the calculation, so we should take it with a grain of salt.
Fantastic meithan, thank you for spotting the typo! And yes, the model I use is quite crude, working basically outside my comfort zone here. I would be happy to adapt your atmosphere model. I want to publish my script once I feel reasonably confident that its correct, is it ok if it contains (full or part) of your code?
I realised that this is much more complex than I thought. I have to fit a physical acceleration profile to the data. But part of the acceleration is eaten by gravity. That part depends on the centrifugal force which in turn depends on the horizontal velocity in orbital reference frame. The data is in ground reference frame and to transform in between the two, my 2D model is not sufficient because I can't model the orbital plane properly. I don't have the time to start over (child and family are more important). Maybe I model the acceleration in the 2D version and we just have to cope with the uncertainty. What do you think?