For those of us programming nerds that want to play with aerodynamics, I can't recommend AeroSandbox enough. While the code is pretty obviously written for people who know their way around aerodynamics and not so much around programming, it is remarkably powerful. You can do all sorts of aerodynamic simulations and is coupled with optimization libraries that allow you to do incredible aerodynamic optimizations. It comes included with some pretty powerful open weight neural network models that can do very accurate estimates of aerodynamic characteristics of airfoils in a fraction of the time that top tier heuristic solvers (like xfoil) can do (which are already several orders of magnitude faster than CFD solvers).
You can't escape momentum exchange. To generate an upward force, the airplane must exert a downward force on the air molecules.
An airfoil does this more efficiently than a flat plate, essentially using the top shape to create a low pressure area that sucks the air over the top downwards, imparting the downwards momentum, along with deflecting the air downward on the bottom surface. A flat plate pitched upwards "stalls" the air on the top surface, because the air has to travel forward some to fill the gap by the plate moving forward - so this creates a lot of drag as the plate is imparting more forward momentum on the air.
The issue is that to analyze lift using momentum, you have to do statisitcal math on a grid of space around the airfoil, which is super complex. So instead, we use concept of pressure with static and dynamic pressure differences creating lift, because it makes sense to most people learning this, which then all gets rolled up into a plot of lift coefficient vs angle of attack.
And as you dive deeper, you learn more analysis tools. For example, there is also another way to analyze performance of an airfoil more accurately, which is called vorticity. If you subtract the average velocity of the airflow around an airfoil, the vector field becomes a circle. In vector math, the total curl of the vector field is directly correlated to the effective lift an airfoil can produce. This method accounts for any shape of the airfoil.
But under the hood its all momentum.
And if, say, airfoil was never discovered, we'd probably design the whole wing slightly differently to compensate for it, so the actual difference wouldn't even be 20%.
Airfoil is about as important as winglets, and planes fly without winglets just fine. But nobody points to winglets and says that's the crucial bit that makes the whole thing work.
To get off the ground Lift > Weight, Thrust > Drag, or to simplify to stay aloft Lift = Weight, Thrust = Drag
Bigger engines weigh more.
To get off the ground you need an engine powerful enough to overcome the drag necessary to generate enough lift.
That is what enabled powered flight especially at the beginning. Wing design with a good enough lift to drag ratio and engine+propeller design that had a good enough thrust to drag ratio to come together for more lift than the aircraft weighed.
Admittedly there is an amazing amount of fluid-dynamic subtly on top of this simple Newtonian problem. But I am surprised that almost no one starts with "An airplane produces lift by moving air down, for steady flight it needs to move exactly as much air mass down as the plane weighs. here are the engineering structures that are used to do this and some mathematical models used to calculate it"
To be more precise, we defined or made a shorthand of this downward force W. Originally it stood for weight but we knew it was the downward force that must be counteracted by an upward force called L for lift. Lift by convention was always an upward force.
These are conventions taught and used.
If we treat the angle where zero lift is generated as the base angle for an airfoil, then all airfoils generate lift depending on their angle relative to that, including a flat plane. As the GP says, other properties are the dominant factor in airfoil geometry.
When introducing airfoils I think it is more useful to start from a plane than a traditional airfoil shape; the math and intuitions are much clearer from there.
It's not finished but I started writing this to clarify: https://entropicthoughts.com/paper-airplane-aerodynamic-stab...
Scroll down to "trim and angle of attack".
(I hope there's nothing embarrassing in there. It's an old, early draft.)
They should receive an unlimited grant to produce educational content for the digital generation’s benefit.
Airfoil - https://news.ycombinator.com/item?id=39526057 - Feb 2024 (296 comments)
1. https://www.grc.nasa.gov/WWW/k-12/VirtualAero/BottleRocket/a...
Even your link explains: "The net fluid force is generated by the pressure acting over the entire surface of a closed body. The pressure varies around a body in a moving fluid because it is related to the fluid momentum (mass times velocity). The velocity varies around the body because of the flow deflection described above."
I.e. pressure differential is experienced as lift and is caused by the flow turning.
Explaining the actual cause of the flow turning and resulting lift (and why attachment is maintained along top surface) requires looking at fluid dynamics/navier-stokes including pressure differentials, viscosity etc. The pressure differentials allow a more comprehensive way of breaking down the forces at play.
I like this video for a more comprehensive understanding without getting too in the weeds with the math: https://www.youtube.com/watch?v=aa2kBZAoXg0
I found his explanation at the 13 minute mark to be hand wavy. He talked about flow turning and momentum change but just hand waved away why pressure is higher at the bottom of the wing.
The way the airflow exerts that force is through pressure differentials: air under the wing having higher pressure than the air above it.
Momentum change can describe physical interactions, and it's often easier to calculate things that way, but actual physical forces still exist, and can also be used to describe the same physical interactions.
https://ciechanow.ski/archives/
For machine learning, Distill.pub has some excellent hands-on tutorials. For example, here's one on momentum:
And going kinda meta, learning about the principles:
Amazing times!
It's a valid fear.
I don’t know how long it takes Ciechanowski to create these explainers, probably a few months? It shows and it’s well worth spending your time reading through his content meticulously.
How long does it take for an LLM to crap out an equivalent explainer? 60 seconds? You should be spending less time than that reading it.
Bartosz Ciechanowski could generate an explainer like this using Claude today if he wanted to. But would he? If someone like him had the mind to do it then they could instead. But where’s it at? These types may hold themselves to a standard above this method. No shame in that.
Seems like you’re contradicting yourself a bit here- is it actually possible to make the sort of explainers from TFA, or is the author operating at a level you can’t touch?
(I hope you don't get downvoted by Chichanowski's fanboys. Sad to see people being against innovation, on this site of all places.)
I think it's only a matter of time, AI history has been a cycle of "yeah, but it will never do this", then literal weeks later it does it, lol.
We should think about how each part of the iteration cycle you describe can be improved. This is definitely a problem that can be solved!
I look forward to Bartosz's articles because they're rock-solid sources of information and the visualizations are both easy-to-understand and surprisingly light on performance. It's all shockingly digestible.
Honestly, as popular science writing goes, this is art as far as I'm concerned, and art is best when it comes from a place of passion and conviction, something AI will never be able to reproduce.
