Using a simple spreasheet, I’ve found how the force of gravity on the balloon changes over time. The gravitational force changes because the balloon moves farther and farther away from the earth.
If you look at the formula for Gravitational force, you’ll notice that little R squared on the bottom. This is the distance between the two objects (M1 & M2). So, as that r distance goes up, the force of gravity goes down. That being said, the 50,000m the balloon flys for changes the gravitational force quite a bit. Now, looking at my spreadsheet (attached), the change in the gravitational force is almost half a newton. Not a large number, but still a significant change all the same. All the best,
Well someone beat me to it. They solved for the ascent rate. Mad props to them because it would’ve taken me much longer.
Now lets see If our data lines up with the data of the launch. The wired article puts the velocities around 3.2 and 4.5 m/s^2.
If we make that into a velocity with an acceleration, 4.5-3.2/600, we get a very small acceleration. From that, I made a simple spreadsheet, and it puts the pop point at around 90 minutes.
On it’s voyage back down lets put the terminal velocity at 193kmph, this puts the total voyage time just over 2 hours. It may be that the acceleration of the balloon is a lesser value. Or maybe the balloon slows down as it rises, but I can’t prove or disprove that. As the balloon gets farther away, the Fg slowly decreases, but I’m not sure how the Force of the balloon changes. Anywho, That all I have for now, all the best, -B.
I tried setting up a ratio of Control f/s over control Pixels/s to Flight f/s (Unknown) to flight P/s. I didn’t work. Here’s the data I got:
I’ve created a SpreadSheet that computes, based on the pixels count of a man’s height and the track radius, a good range of speeds, centripetal accelerations, track length, Car velocity, forces on the cable and which types of rope or cable have the ability to handle the force. This spreadsheet can also be used for any centripetal acceleration problem for a video. Simple plug in the Constants Pixel height, Your guess of the Constants Meter height (Fill in cell B2 and the spreadsheet populates in steps of.05), and the track radius pixel length. Then It shows neat facts like your track radius in meter, and track length. From there, plug in a period time and a mass, and you have object velocity and centripetal acceleration, along with forces.
Using the above spreadsheet, I’ve analysed this video of a RC claiming to be going 200 mph. Plugging in the variables mentioned above, I have found that there actually is a pretty good chance that car was going around 200 miles per hour. You stay classy internet
I tried another method of finding the height today. I compared a pictures who’s subjects were similar lengths in pixels. I then compared there actual length to height off the ground. It didn’t work. I calculated that the balloon went down. Oh well. It looks as if I must resort to Focal Length. Which I need some serious help on. Cool beans.
Edit: took a look at focal length stuff.
[distance to object (mm) = focal length (mm) * real height of the object (mm) * image height (pixels)] / [object height (pixels) * sensor height (mm)]
The thing I don't understand is how I find the focal length to begin with. Or the sensor height
Indeed I do believe it is going at the said 200 Miles per hour that they stated. For further reference, please enjoy my spreadsheet below. This also means the height of the man stooping is five foot, three and three fifths inches tall. Snazzy. Now the question is how much this bugger weights, but I don’t think I’ll be able to find that out based on the video. That also means that the material they used can also not be determined. Very well. You stay classy internet,
Nate uploaded the SpaceCats camera calibration video today. I got 3 screenshots, one with the camera at 3, 6, and 9 feet.
Picture one: (855, 328) -> (850, 643). Pixel length: 315 pixels.
Picture two: (866, 434) -> (863, 599). Pixel length: 165
Picture 3: (583, 582) -> (852, 498). Pixel length: 84 pixels.
So I think this data shows that there isn’t a direct relationship between the Pixels per meter ratio and the target distance… Hm. After plugging these numbers into my calculator, it gave me a linear and quadratic regression.
Linear: -121x + 1318
Quadratic: 12X^2 + -266x +1683
I feel the quadratic to be more accurate, but I would like a second opinion on that.
I think I need some help. -Beau
I did some more measurements on the 200 mph car video. The 240p resolution didn’t help me much, but I think I got some solid data. The first picture is the screenshot I used to capture pixels to man height. The second is the spreadsheet I set up to calculate rang of track radius. Take a look,
I took 3 screenshot of out video all from different heights. I will measure the ratio of Pixels to actual Length. From this, I think I will be able to find the height at each point.
Picture 1: (813, 445) to (827, 406), 14^2+39^2=1717, so length is 41.44 pixels, which equates to a certain distance (That I need to find) [The distance between the edge of the rectangle to the semicircle on Broyles patio]
Picture 2: (984, 545) to (838, 594), 146^2 + 49^2 = 23,717, so the length is 154 pixels, which equates to 100 yards of the Westminster football field.
Picture 3: (1470, 228) to (1515, 304), 45^2 + 76^2 = 7,801, so the length is 88 pixels which equates to 155 feet of a baseball diamond.
Tomorrow my plan is to measure that distance on Broyles patio. Then i’ll set up a test . Ill position the camera 30 feet away and foot a 1 foot ruler in front of it. Then I can say at 30 feet, 1 foot was x pixels. So, at Y feet 154 pixels was 300 feet. Kool stuff.
I just got back from retrieving my high altitude weather balloon. Here are some considerations: We have no idea the rate of accent/max altitude/rate of decent. I was thinking I could use the 27 minutes of video that we have to measure the accent rate. I know that the balloon accelerated pretty quickly, but need to affirm this in the video. My method will to take a series of pictures from different heights and measure Pixel to WMS stadium ratio. Graph that, and see if it results in a linear relationship. Now all I’m waiting for is a video. All the best,