Circus Club Almere
Hi all, Just a quick ad for our new workshop here in Almere in the Netherlands. https://jugglingedge.com/club.php?ClubID=1838
We've got a great space for it. Hoping to get some local interest!
I am a 15 year old juggler and I really really want to go to the Fort Wayne IJA festival because it is the only festival that is within a 2 hour drive and within my time constraints. But since I am 15 (16 by the time of the festival) My Mom wants as much information as possible and a soon as possible. However I haven't really been able to find much information about it other than the location and date. Am I looking in the wrong spots or im I just to early because I was looking for like a sedule of the performances and competition times. If not out yet When could I expect to see the sedule?
And information about it would be helpfull
I had a quick look at the IJA page and I don't think there is much information there about this year's festival yet. However, if you click the "past festivals" you could find some schedules from previous years, that could give you a rough idea if this is your first festival.
I have only been to the IJA festival once, last year, so I bet there are people here on the Edge who knows more than I do.
I'm starting a new juggling club in Plymouth, Devon UK in a couple of weeks.
First meeting on 15th January.
Juggling and club passing, unicycling, hula hoops, poi, staff, diabolo, etc etc...
All skill levels welcome. Primarily for adults, (although enthusiastic under 18’s are welcome if accompanied by an adult).
Stoke Damerel Parish Centre
Tuesdays term time 7:30-9:30pm
£5 (£3 unwaged)
Stoke Damerel Parish Centre
behind Stoke Damerel Church
Stoke Plymouth PL1 5QL
After several years of searching for a venue to hold their festival the Cascade Jugglers Association has partnered with Seattle's School of Acrobatics and New Circus Arts (SANCA) to present the new Seattle Juggling Festival. Come join your Pacific Northwest juggling and flow arts friends at SANCA for the weekend before Memorial Day for juggling and flow arts fun and workshops.
See https://seattlejugglingfestival.org for deatials
If you like whips and physics as much as I do, this might be the best ten minutes of your day.
Found in this thread at the very lovely /r/shockwaveporn.
There's a load of the usual like and subscribe bullshit at the end, but the rest is totes ossum. Enjoy.
Always nice when worlds collide!
I was a bit surprised that they'd originally thought that the fastest point was going to be at the end. My guess is that intuitively, they were thinking about acceleration (or jerk) causing the sound, even though theoretically they knew it was all about speed.
What do you mean? The 'fastest point' does not equal 'the point that creates the sound'.
If the speed of sound is reached before the end of the strand, wouldn't you imagine the rest of the whip to keep on speeding up afterwards?
I watched back the video, and this idea of mine is can not be seen at all. Maybe the acceleration should take place but it is disturbed by the shock wave, or maybe something else is going on, I don't know much about physics to be honest. They haven't figured what happens to the tip in the last bit either (8:09 in the video)....
No, I wouldn't imagine the whip would maintain the very speed (or accelerate) into the full extension. I the tip hits its max speed after the whip has a toboggan shape and before it gets to a Chinese spoon angle (I see it as hitting its max speed close to, maybe just slightly after, a Nike smoosh).
The whip appeared to only be going over the speed of sound for a very brief period of time. Sure, its max speed and point at which it breaks the speed of sound could be slightly different, but neither appear close to the full extension of the whip.
It's only using the 3D modelling that they couldn't see what was going on at the end of the whip. The (very) high speed camera using the Schlieren method seemed to capture it well.
You got me curious and I looked up the two paper references in the video because I figured they'd have an equation for the speed. Better, they have a nice diagram. Looks like the toboggan angle is actually the winner!
From the Arizona people: http://www.e-kaczor.net/keiko/whip.pdf
I don’t know if the authors have or haven’t mentioned this but here is an older link to whip wave modelling
How to Build a Claude Shannon Juggling Machine - video and instructions here: https://www.instructables.com/id/How-to-Build-a-Claude-Shannon-Juggling-Machine/
Building is not my thing, but it was still interesting to watch and hear about his learning process and how he experimented and adjusted to make the corrections needed to get it reliable.
I built a Claude Shannon Juggling Machine. Instead of using physical objects, I built this machine virtually. This physics simulation is written in Python 3. The UI and some of the functions use the computer vision software library OpenCV. Like Scott said in the original post, the fun of this device is not in building it. The interesting part is tuning the device so that it juggles.
This program is object-oriented. The balls are the objects. Each ball object has two attributes, (1) a tuple to describe the ball's (x,y) coordinates, and (2) a tuple to describe the ball's velocity vector (speed and direction).
Several functions allow the ball to interact with the environment. These functions move the ball, apply gravity, bounce the ball off an object, etc... In the main loop of the program, all of these functions are called on the balls to produce juggling.
The machine is tuned by adjusting the parameters. The parameters are defined before running the program, or changed during runtime using the keyboard. The most important parameters are speed and rotation. Each number of balls requires a specific combination of speed and rotation to juggle. This graph shows the combinations of speed and rotation that work for 3, 5, 7, 9, and 11 balls.
To find these values, I tuned the machine during runtime. It was tedious to tune the machine, and I am searching for a way to mathematically derive the parameters that will produce juggling for n number of balls. Is there a formula that relates the number of balls and the combination of speed and rotation?
Please try this out for yourself: Link to Code on Github
Video: Link to video on juggling.tv
Link to Gifs: Gifs on Imgur
I can use linear regression to predict values that will work for 13 balls, using the known solutions for 3,5,7,9, and 11 balls. I'd like a way to compute a solution for n-number of balls that does not involve using experimental data.
Very nice simulation, thanks for sharing it.
I did some simple spreadsheeting on your results. While the speed and rotation are roughly linearly related (R2 = 0.98) the speed is better correlated with the log of the number of balls (R2 = 0.99 for a log fit and 0.93 for a linear fit).
It might be that you could get better correlations by slightly adjusting your speed and rotation estimates. How do you decide what are the best parameters for each number of balls? Can you get it to juggle for all the different balls with a forced perfect linear relationship between speed and rotation?
I didn’t see any reference to masses in your code. I think that implies the paddle and the floor effectively have infinite mass and don’t move due to the balls hitting them. It might be simpler to see the underlying physics if the collisions were perfectly elastic. It could help me to know the units of time, distance and gravity to try to relate it to Newtonian physics.
I found these parameters by trial and error. The program allows me to adjust the parameters during runtime. I ran the program and manually adjusted the parameters until the machine achieved juggling. The parameters that I found are not optimal, but the best that I could do. Tuning this machine is difficult because changing one variable effects the whole system.
The machine will juggle if the parameters are in the correct range. For example, the optimum speed for 5 balls is 0.0148, but all values between 0.014 and 0.016 are valid for juggling. The ball will hit the middle of the paddle when the parameters are optimized.
There are no masses in my code, which by the way is not quite an accurate physics simulation. Here is some more info about the units:
angle, speed = addVectors((angle, speed), gravity_vector)
When the balls bounce off the floor, they return with 75% of the energy. This makes juggling easier. Because the balls loose energy in the bounce, they can be thrown at the top of the stroke and caught at the bottom of the stroke. This helps avoid collisions.
When the balls are released from the paddle, they are released with the same velocity vector as the nearest part of the paddle.
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