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I wonder if anyone has attempted to use machine learning to try and build a better paper airplane. I feel like that would be super interesting.


If you give me a realistic physics environment to train an agent in I'll do it for you.


Hmmmmmm. I wonder if X-Plane would be capable of simulating that... they basically do an FEA model of flight, although I’m not sure if it would scale down appropriately.


X-Plane really only SORT of models flight. There is no actual FEA or fluid simulation of any kind. The airfoils are canned data lookup. So you can't make something out of polygons and have it wactually "work". It'll fuselage calculate drag based on frontal area and the coefficient you specify, but that's about it.

This approach works well for real planes since 99.999% of them use standard NACA airfoils that are well documented in the public domain.


Oh! Thanks! I've flipped it into the "airflow visualization mode" but didn't know that it was based on lookup tables!


Flight physics don't scale down (or up) well. It's the predominant reason small airplane and quad models have enormously unscalable performance characteristics and abilities.

Making it bigger doesn't "just work"... same for the inverse.


Isn't that mostly due to the square/cube nature of scaling things? E.g. your wing area changes with the square of your scaling factor, but your mass changes with the cube of your scaling factor?


I think the physics mostly DO scale down, it's air density and gravity that don't.


I wonder if anyone has attempted to use machine learning to try and build a realistic physics environment. I feel like that would be super interesting.


Many people have attempted, but its still and unsolved problem with fluid physics.


Maybe we're already living in it? ;)


Not too far from it: "Pteromys: Interactive Design and Optimization of Free-formed Free-flight Model Airplanes"

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.648...


I want to see someone use the dandelion seeds method in a paper airplane. Many cuts required haha




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