Відео

Woble gooble alien texture

Terry Chad Davis

videos like these are what internet was made for

I understood none of this yet I was glued to it all the way through

Could write conflicts also be avoided by just writing to a separate buffer fhan the one you are reading from?

imagine putting a few ai's in there, make them evolve, adapt to the environment and make them learn how to utilise it to its advantage

i just came from your fluid sim video and this channel does not disappoint this was such a simple yet good way of explaining perlin noise thanks for the explanation!

thanks so much all the other videos about water simulation is either way too complicated or just a blender tutorial

This is super cool, keep it up!

This guy's gonna love learning about the weak fem form for the constitutive eularian fluid equations

there are these drills that can make triangle or square holes. Some people also used them to draw a shape with turning a crank and a lazer pointer mounted on some gears. Is that more or less complicated than Bézier, since I'm not even able to find the right terms?

In a way, this is functionally simulating Quantum Mechanics and illustrating the principle of "Particle/Wave duality". The entire fluid motion can be represented as a vector. But the vector, *itself,* must behave as a particle, moving in response to the overall "equation" of the fluid flow. And that flow, in turn, changes in response to how those velocities keep changing within it. The more "interactions" there are, the more you'd have to "zoom in" and re-calculate based on the rapidly changing velocities. But the fewer the interactions, whether that be due to smooth flow, "low temperatures" (less movement), etc., the more you can just look at the overall average equation for how the vectors evolve. So, in keeping with this notion that this is very much like Quantum Mechanics, using the principles of QM would probably help improve the quality of the simulation. *1)* Non-Zero Baseline: In QM, particularly Quantum Field Theory, one of the major notions is that everything isn't sitting at a baseline _zero_ state. Rather, there's a certain minimum baseline energy already present, and it's the net _difference_ over *or under* that baseline which is considered. To put it in context of a fluid, since we're discussing fluid dynamics, it's like there's a big ocean of energy already sitting there. How deep that ocean is is a question scientists argue over endlessly, but it's what happens at the surface that is actually important and what they more or less agree on. *2)* Constant Activity: There are constant "little ripples" going all over the place. The surface of the ocean isn't still; it's always churning and bubbling and mixing; and as those little micro-waves this motion generates interact with one another, the peaks of the waves amplify one another, the dips amplify one another, but where peak and dip meet they cancel out. And when it churns enough, it gets big enough to be called a true "wave" (a particle like an electron or a quark). You can't really say that an ocean wave has one specific location; it's a "part" of the ocean as a whole. But you could also point at a part of the ocean at any given time and ask, "Is this currently part of a wave?" Maybe yes, maybe no. The bigger and stronger the wave, the more likely you'll be to "catch" it. *3)* Quantized: This means that a wave can't be an arbitrary "height" in this ocean (where "height" here is a stand-in term for the "energy" of a particle). It would be as if waves can only be increments of 10 meters in height. Anything between 10 meters below the surface and 10 meters above the surface would effectively register as if it were right at the surface. Functionally, what this is is "statistical rounding". If there were a wave (particle) that could potentially be 17 meters tall according to the vector math, the particle math has no clue what that means. Particle math only deals in increments of 10 meters. So it has to round 17 meters; but it doesn't use formal rounding. Instead, it uses statistical, trigonometric rounding. 17 meters is 0.7 of the way from 10 to 20. I forget the exact formula, but it's 50/50 if it were X.5, but more than a mere 70% chance at X.7 to round up to the higher value (it follows trigonometric values around a unit circle). So these aspects could possibly be implemented in the following ways. First, have some non-zero "baseline" flow value. Never have "zero flow". Not zero *actual* flow, anyway. But simulate the actual pertinent _movement_ not based on this "real baseline" but, rather, relative value compared to that baseline. So, for example, if baseline flow has a vector weight of, lets say, 100, your actual fluid movement model *treats* 100 as if it were zero (staying still), and then movement of 105 is going 5 _faster_ than that. Next, have micro-purturbation in the model by allowing that baseline value to "jitter". While baseline flow that's considered "stillness" would still be considered 100, any specific "cell" of fluid would randomly, iteration to iteration, have a value between 98-102. And it can change its value by up to 2 either positive or negative. These will still factor into calculations, so these changes won't "come from nowhere"; if micro-flow is generated, it will pull from surrounding cells. Lastly, when it comes to evaluating how the vectors, themselves move, you can "fudge" the value a bit. Round it based on the statistical rounding I described to let it "zoom out" and use lower resolution, and then do more of a "random step" pattern instead of a complete vector calculation to determine how a vector moves. This way, vectors don't have to consider, "how am I moving based on everything around me" 100 times, they just have to decide, "how likely is it for me to move up, down, left, or right based on forces around me" 100 times.

I went searching for a visualisation exactly like this one to help me understand, got exactly what i needed! Good work!!!

Thanks for the explanations and the sources! please add the links to the description though :D

Very nice video. Now get a beefy graphics card and run at very high resolutions lol.

Hey i wanted to send masked image from a webcam using python only as that code is doing many things more so i am left with only this option to send image from python to unity can u help me with that

Now I have to find someone to explain how to do that in Godot

Imagine the kind of simulation you could do with a 4090 over the mac book.

Thank you for these videos! I often have the same thoughts about being/experiencing places that would be impossible to get to, and making sims to make it possible, but I’m always so unmotivated to do it. So thank you for not just exploring these questions, but for also making videos to share your work with us!

i bet this would run much better on a gpu with a cooling system and more than 10 cores (or whatever your model of macbook has)

me: 50 frames per second that’s pretty bad performance RL: *”on my MacBook Air”* thats CRAZY

this thumbnail is better

love the experimental feel to how you moved forward itteration by itteration,

rather than updating a bunch of nonadjacent cells why don't you store two buffers, and instead of changing a cell's neighbors, instead calculate how a cell is affected by its neighbors, and write that into the second buffer.

Great visualization!

Which method is cheaper to run?

11:11 that looks like the lines of a magnet.

no links to the code?

nice but I don't understand this sentence "When vector points into below right cell cell is green"

Thank you for this video

Awesome 👍

Nice

You could have used MultiGrid for the solver since it land it self to parallelism better

Can't believe I watched entire video about coding and didn't get bored

thanks for such a great explanation : ) . I 💙it

Very nice explanation. Keep it up.

No way Euler got named for a fluid dynamics problem. We're supposed to name the problem after the *second* person to solve it!

Finally good explanation

Use a mac with any non apple monitor and it destroys those bezier curves

first thing I thought about when I clicked on this video is about The Powder Toy which is a pixel based particle simulator game which actually has that exact same type of fluid simulation for simulating air in the game

thumbs up. For me, the three Lerp explanation was beautifully succint.

So persistent zero velocity is like a solid object? I wish it were easier to see it against an unmoving background .

wait you need a macbook pro to do pro stuff?? (looks sexy)

Awesome made my day :))

Finally secret revealed

loved the video! feels like discovering sebastian lagues yt channel all over again :)

Today is the first time I actually understood the bezier curve

That was one of the best explanations for advection I've seen online! Especially the pushing bubbles out of a phone screen protector analogy.

Cool

Nice 😊