Rigid body simulations are much much simpler. There’s a siggraph course from 2001 [0] which is a bit of a dense read but it will bring you all the way up to a full blown rigid body simulation and understanding the math behind it too.

[0] https://graphics.pixar.com/pbm2001/pdf/notesg.pdf

One thing that helped me was doing some tutorials for pico-8, an intentionally 'weak' game platform, one of which is a platform game with a simple / understandable inertia / gravity simulation (jumping, running left/right; think Mario). It was understandable enough with an x / y position for the character and a delta-x / delta-y representing their current speed. Every frame the dx / dy would get changed depending on player input and/or character state.

Ex: if player presses jump button, set state to 'jumping' and dy to 1. Every frame, dy = dy * 0.9. When dy <= 0, set state to 'falling'. Every frame, dy = dy * 1.1 until dy = 1 (terminal velocity). Then add some collision detection.

I think those basics are also behind the simpler physics simulations, the 'falling sand' types would be ideal for an application like this.

For statistical mechanics, I really liked [1]. Comes with loads of python programs.

To see what might peak you interest, the videos in [2] could be a good starting point.

[1]: https://www.coursera.org/learn/statistical-mechanics

[2]: https://matthias-research.github.io/pages/tenMinutePhysics/i...

The Nature of Code by Daniel Shiffman is an excellent entry point - it teaches fundamentals of physics simulations with clear examples in Processing/p5.js.

Just go to Perplexity or something like that, its well trodden ground. And essentially, what you're doing is discretizing the relevant differential equations and getting that to run in a 2D or 3D cellular automaton.

I'll give you a simple example. For diffusion of heat between 2 points, the rate of change (first derivative) is proportional to the difference in temp between them. So you make an update rule for points on a grid that says "calc the average difference of a cell's temp with that of its neighbors, multiply by some constant, and that is the amount to update this cell at this time. Run that for every cell in parallel, many times." Then you tack on a visualization and you can watch the heat diffuse. A fun example would be the cooling of the proto-Earth. You can watch the crust form.

Heat diffusion is a good starter problem. So is gravitational interaction.

Probably what you want is "numerical methods" and "computational physics".

"Physical simulation" is a very broad scope, so your code for simulating fluids is going to be very different from your code for simulating planetary orbits, and at times it may feel a bit ad hoc. But at its foundation physical laws are written in differential equations and linear algebra.

So whatever algorithm lets you numerically integrate several inter-related variables is going to be broadly applicable to simulating any physical phenomena. At the simplest end of the spectrum you just naively approximate integration by brute force. Eg at each step just update your physical state variables by doing velocity += acceleration, position += velocity. This is called Euler's method, and while simple, it accumulates unacceptable errors rather quickly in most circumstance. The more advanced approach is to use a method like Runge Kutta. In circumstances where you have some known property, like say energy conservation, you can implement a method which explicitly imposes the constraint. This is good for cases where the motion is highly periodic as it prevents the numerical error from accumulating exponentially in orbits that spiral out of control.

Of course at some point you'll have to grapple with the issue of if you are simulating trajectories of free particles or values of neighboring grid points in a field. This question of how best to encode physical systems and simulate them cuts to the heart of physics.

I'll leave it at the old cliche "information is physical"

"I can't belllieeeve RMDNZ preferred L-Johnson's card to mine"

Practically pregnant with electric potential

You can get boards like these made for single-digit dollars per unit* even at prototype scale, through companies like jlcpcb.

*I haven't looked at the specific parts for this board, the LEDs look nice and could be a little pricey.

Electronics can be surprisingly easy and cheap to build these days. He designed the circuit and layout with software called KiCAD (free and open source) then submitted the designs to a fabrication house - probably a popular offshore one - that easily can handle that level of board and component placement complexity. It would probably cost only a few hundred to build and ship, with 1 month turnaround time.

You can also hand-assemble surface mount parts by applying solder paste carefully to the pads, then placing all the components on the paste and heating the board until all the solder melts. That would have very time consuming for all those LEDs!

>He must have worked with a company that can do the surface mount assembly

He did (there are centroid files in the production folder, which tell the board house where to put the components), but you'd be surprised at how possible it is to assemble something like this by hand. You won't believe me, but I find it easier than through-hole soldering (because you don't have to keep flipping the board over).

But there's a 99.9% chance this was done in-house at JLC or PCBWay.

Yeah, wondering how the LEDs were aligned so precisely. Some kind of silicone grid-like jig to hold them while the solder reflows? Or is it just pick & place robotics doing what they do with precision?

How much does it cost? The guest passes for hacker conferences are full-on computers these days, if this is in the same price bracket it would be a great idea for those.

GPT-o3 estimates it'd be $10 to $20 cost to make these. I could see someone running a niche business selling these (e.g. enterprise software sales rep trying to stand out).

I half expected this to have a button/mode to show custom QR codes...

Maybe you wouldn’t give em to just anybody, but anybody who gets one is guaranteed to remember you!

I’d probably even keep it in my desk to play with. After a few weeks I’d accidentally have this guy’s email/linkedin memorized for eternity

I'd include a sad tomagotchi that after a week or so guilt tripped you into giving it back, its heart broken, missing its original owner.

small ad-hoc networks like that with IR and early bluetooth were a lot of fun.

I love it; I bought a secondhand Palm just before smartphones became a thing for cheap and had a lot of fun with it. I wonder if I still have it somewhere and whether it still works, I haven't seen it in ages though so probably not.

Ha! That's pretty cool.

My first thought with this card was that it could be "gamified" into something that kids would probably love. A clique-y, social thing where kids could "pour" some of their fluid into another's card, with NFC or something. User preference colors that don't change when "poured" could help indicate how many different people have interacted with your card.

But enough spitballing. There's no killer idea there. Just something I'll be amused to see show up as a value-add for some other kind of toy, or whatever.

Do you use any of the features? This is kinda cool, I love when people pack way too many features into a single product :P

That was very clearly mentioned and linked in the article, too.

+1 for mitxela, dude never ceases to amaze

The circle works much better for the fluid simulation.

Is there a Digital Disco Ball?

That’s cred, man. Real cred.

Wack font. Circuits exposed. Pixels with fat borders between them. An ugly charging port. But more stuff, packed into a small sleek volume than reasonably possible. Working perfectly.

That’s not Jobs. Oh, no. It’s effing Woz.

The guy is a true hardware engineer.

It is.

rather it's even smaller, it simply has the inner part of a usb c connector - exactly the thickness of the pcb

similar to https://github.com/cnlohr/ch32v003_3digit_lcd_usb/

Thought the same but from what I can see those are somewhat uncommon, presumably you are unable to affix them to the board as securely as the typical connectors

The images in the GitHub show that the card has this.

In the implementation, the design uses a 'card edge' type connector with the whole PCB fitting into the constraint of the thickness of the center blade of the USB-C connector. So when charging, the board slots into the cable-end connector, and when not charging there is only the PCB. The PCB has cut-outs for the cable-end connector to fit into the PCB -- so like you're saying, but even thinner.

Agreed. I'd never hire this embedded system engineer to do graphic design. /s

That and the overlapping silkscreen hurt to see, but otherwise a super cool project. Although they're very minor things that don't technically matter, it can give off certain impressions to people.