I disagree. We know exactly why they work because they are using Finite Element Analysis to test them, just like we would with any other part.

In fact, the neat part about this process is that they are basically using FEA in reverse to create them. So we're using math that we know works from zillions of different validations on traditional parts - and feeding that into an algorithm that just connects the load point dots in the most efficient way possible given certain constraints.

So I would say it's more reliable than you give it credit for.

But the biggest downside, and the reason you won't probably ever see this style of design used more widely is that manufacturability is a huge pain and/or expensive. Outside of 3D printing technology, these things are very hard to actually construct.

Kinda indistinguishable if it works all the same. Either way, nobody knows how the heck it works, but it works.

FEA is actually part of the generation process... It's basically iterating different designs and validating many times. So the output of the process is already at least FEA validated. You would then do all the additional validation that you would typically do on a classically designed part as well.

The line between a procedural algorithm and AI is pretty blurry. The term AI is thrown around a LOT to describe things that would have never been described as AI 10 years ago despite being the exact same code.

I think the idea that most parts aren't already bespoke is a misconception. Everything structural on a rocket or space craft is bespoke. Only built for that craft. Maybe only built a handful of times. So that part is nothing new.

Validation for these designs would be no different than anything else. Finite Element Analisys (FEA) would be used first to evaluate the structure and any changes required to meet the specification would be made before prototyping.

However, what's neat about these procedurally generated parts is that it basically is FEA in reverse. Instead of doing design iteration from idea to part - you just tell it the specification and it designs a part that meets that out of the gate.

The only real downside is that you're much more limited on manufacturability. Either it can't be made using traditional methods and requires 3D printing. Or maybe it can be made on a CNC milling machine but it requires a 7+ axis machine center and takes 100x longer to make. Which for some parts might actually be fine, but for others the added cost would never make sense.

Really interesting topic I'd say.

Yes. These designs are basically highly optimized, non-uniform load structures. You validate their load capability the same way you validate complex parts designed by humans: finite element analysis (FEA).

Edit: FEA is how you validate before your first prototype is made. You also CNC or 3D print a prototype and physically stress it just like any other part. Design validation is NOT just done on paper. It also is done on prototypes made using non-production equipment / tooling.

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A big one is that designing with this process means at every step you are highly dependent on complex software modeling. Instead of using well known design rules to develop your design, you have to run a sophisticated algorithm that probably needs a hefty amount of compute power. Then you have to run FEA on literally every part, again needing lots of resources. That kind of software isn’t cheap and neither are the computer clusters.

Also, you have to put a lot of effort into defining your requirements very precisely and uncovering hidden requirements. For example, if you need a lot of strength in a part do you need that in both directions or only one? If you only need strength in one direction the best solution might be a steel cable, but I don’t know if there algorithms would consider that.

There’s also part integration. Things have to be designed for manufacturing and service (part tolerance stack up, order of operations, tool and hand clearances, etc.)

You also have to carefully consider your validation and what assumptions it makes about the parts that might no longer be true.

In the end, generative design is probably only worth the effort for specific parts or even portions of those parts, not the whole product.

> If we didn’t know what we were doing this stuff wouldn’t work.

You are more right than you know...

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Is it possible to do design validation for designs like in the article?

What do you think are the downsides?

Someone else mentioned standards. It's impossible to standardize anything when everything is bespoke. What else?

That's fine but the main thrust of my point (hence why I lead with it) is there ARE downsides. And they didn't discuss those which makes this article less good because I'd already heard about them doing this stuff. I knew it was being used, and while this article did elaborate more than some random scimag article I read 7 years ago that was talking in theoretical terms, it should have also elaborated more on the downsides because this type of writing is almost sensationalistic when that is the exact opposite that I want from science journalism. I want to know the whole truth.

Aerospace is completely different to building design.

In aerospace designs are custom out of necessity due to each part being highly mass optimized, interdependent on other parts and having different design goals and trade offs from project to project. Also, each part is highly validated and inspected as well as painstakingly assembled in (usually) very clean environments. The exact safety factor of the product is well known and controlled to a low ratio.

In building design, designs are using either commodity parts or commodity materials that are produced too much less exacting precision, often made on site exposed to the elements. So design knows the exact safety factor isn’t known and needs to be large to make up for this. There’s also always human lives at risk.

So building design rightfully has to be very conservative, regulated and has no impetus to change quickly. Aerospace design has to be less prescriptive and less safe just to make it to orbit. That doesn’t mean there’s not a ton of very good engineering involved in both fields, it just means more design freedom for aerospace.

If you mean they're using topology optimization instead of generative design, how would you know?

I think the AI is using the same software tools as humans are to analyze each iteration's strength - it's not thinking in some alien language. Also it's reacting to prompts and parameters set by humans. The only difference is it has the patience to brute-force every possible solution, whereas human engineers usually think in terms of what they've seen before.

I think all the issues you've laid out are issues that any large and sophisticated project would face, not specifically an Ai-powered one.

Maybe in part due to size limitations. The pictures show parts manufactured in a powder bed. The article then goes on to say they‘re still designed around conventional milling. So who knows.

I agree that downsides should be discussed along with benefits.

I disagree that we don’t know how they work. Part of the process of generating these designs is defining the interfaces to other parts, the loads and the pass/fail criteria. You literally have to define how it works to the algorithm to get the design in the first place.

If you get those things wrong, even classically designed parts can fail. Garbage in yields garbage out.

This is also the reason for validation. Validation often finds unanticipated or misunderstood interactions and manufacturing defects. Which is why it’s needed regardless of design method.

And if a part fails, then you know something in the process (design or manufacturing) is flawed and you chase down the root cause, find an effective solution and correct the process that produced the issue.

Basically, it’s all standard engineering practices for bespoke designs. It’s not easy, but it’s nothing new.

Acronyms, initialisms, abbreviations, contractions, and other phrases which expand to something larger, that I've seen in this thread:

|Fewer Letters|More Letters| |-------|---------|---| |HLS|Human Landing System (Artemis)| |SN|(Raptor/Starship) Serial Number|

|Jargon|Definition| |-------|---------|---| |Raptor|Methane-fueled rocket engine under development by SpaceX| |Starlink|SpaceX's world-wide satellite broadband constellation|

^(4 acronyms in this thread; )^(the most compressed thread commented on today)^( has 11 acronyms.)
^([Thread #8567 for this sub, first seen 15th Feb 2023, 12:34]) ^[FAQ] ^([Full list]) ^[Contact] ^([Source code])

I guess that explains why Blue Origin only barely dips their rocket into (the coldness of) space 🤔

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I think that major problem is nothing in these designs can be certified to be built to any form of technical standard or building code.

We see this problem in the nuclear industry all the time- its very difficult to advance new building codes when you are locked into ASME / ASTM and 10CFR because they all rely on underlying codes (B31, B51) which are built on decades old, proven design. Everything in Nuclear is mission critical, and I would imagine it's the same in Space travel. High quality, proven design, based on established codes and known calculations to back them up. That is proper engineering design.

Different methods, yours created by algorithm, their's by ai.

I would have appreciated if they highlighted some of the downsides in this article. There is always a downside. Just off the top of my head, we know that these "thousands of bespoke parts" work, but we don't know how they work precisely. They can make predictions and hopefully nothing breaks in a way we don't understand (because it works in a way we don't understand) but as projects become increasingly sophisticated with more and more moving parts and separate contracts layers of siloed bureaucracy... eventually the people that designed part A will make something that interacts with part L in a way that they didn't predict because the parts weren't designed in concert from the ground up. They were designed separately and artificially. The parameters were known but parameters change. Mistakes also happen. How resilient will these parts be when suprises happen?

Really interesting read. Thanks for posting. I had never heard of 'generative design' before. :)