For the more low-level stuff there's the FEniCS project[1], for solving PDEs using fairly straight forward Python code like this[2]. When I say fairly straight forward, I mean it follows the math pretty closely, it's not exactly high-school level stuff.
Interesting. Please bear with me as this is going off 25 year old memories, but my memory is that the workflow for using FEA tools was: Model in some 3D modelling engineering tool (e.g. SolidWorks), ansys to run FEA, iterate if needed, prototype, iterate.
So to have anything useful, you need that entire pipeline? For hobbyists, I assume we need this stack. What are the popular modelling tools?
To get started with Fenics you can maybe use the FEATool GUI, which makes it easier to set up FEA models, and also export Python simulation scripts to learn or modify the Fenics syntax [1].
Yeah not my domain so wouldn't really know. For FEniCS I know Gmsh[1] was used. There's some work[2][3] been done to integrate FEniCS with FreeCAD. It seems FreeCAD also supports[4] other FEM solvers.
But, I guess you get what you pay for in this space still.
Electronics (when you start to care about EMI or antenna design), model airplanes (for aerodynamics), rocketry, machining (especially if you want to get into SPIF), robotics, 3-D printing (especially for topology optimization), basically anything that deals with designing solid structures in the physical world. Also, computer graphics, including video games.
Unfortunately the barrier to entry is too high for most hobbyists in these fields to use FEM right now.
There are some obvious downsides and exceptions to this sentiment, but on balance, I really appreciate how the expansive access to information via the internet has fostered this phenomenon: where an unremarkable fella with a dusty media studies degree, a well-equipped garage, and probably too much free time can engineer and construct robotic machines, implement/tweak machine vision mechanisms, microwave radio transceivers, nanometer-scale measurements using laser diodes and optical interferometry, deep-sky astrophotography, etc., etc..
Of course, with burgeoning curiosity and expanding access to surplus university science lab equipment, comes armchair experts and the potential for insufferability[0]. It’s crucial to maintain perspective and be mindful of just how little any one person (especially a person with a media studies degree) can possibly know.
[0] I’m pretty sure “insufferability” isn’t a real word. [Edit: don’t use an asterisk for footnotes.]
> comes armchair experts and the potential for insufferability
Hey, I resemble that remark! I'd be maybe a little less armchair with more surplus equipment access, but maybe no less insufferable.
By all accounts, though, a degree of insufferability is no bar to doing worthwhile work; Socrates, Galileo, Newton, Babbage, and Heaviside were all apparently quite insufferable, perhaps as much so as that homeless guy who yells at you about adrenochrome when you walk by his park encampment. (Don't fall into the trap of thinking it's an advantage, though.) Getting sidetracked by trivialities and delusions is a greater risk. Most people spend their whole lives on it.
As for how little any person can know, you can certainly know more than anyone who lived a century ago: more than Einstein, more than Edison, more than Noether, more than Tesla, more than Gauss. Any one of the hobbies you named will put you in contact with information they never had, and you can draw on a century or more of academic literature they didn't have, thanks to Libgen and Sci-Hub (and thus Bitcoin).
And it's easy to know more than an average doctorate holder; all you have to do is study, but not forget everything you study the way university students do, and not fall into traps like ancient aliens and the like. I mean, you can still do good work if you believe in ancient aliens (Newton and Tesla certainly believed dumber things) but probably not good archeological work.
Don't be discouraged by prejudice against autodidacts. Lagrange, Heaviside, and du Châtelet were autodidacts, and Ptolemy seems to have been as well. And they didn't even have Wikipedia or Debian! Nobody gets a Nobel for passing a lot of exams.
IMO, the mathematics underlying finite element methods and related subjects — finite element exterior calculus comes immediately to mind — are interesting enough to constitute a hobby in their own right.
FEniCs is mostly used by academic researchers, I used it for FEM modelling in magnetic for e.g. where the sorts of problems we wanted to solve you can’t do in a commercial package.
For the more low-level stuff there's the FEniCS project[1], for solving PDEs using fairly straight forward Python code like this[2]. When I say fairly straight forward, I mean it follows the math pretty closely, it's not exactly high-school level stuff.
[1]: https://fenicsproject.org/
[2]: https://jsdokken.com/dolfinx-tutorial/chapter2/linearelastic...