Is structural design an inverse problem? (ASCE paper, free version available)

[u/StructuresEngineer81]

Curious what others think of this ASCE Forum paper (links below). It argues that structural design is fundamentally an inverse problem: structural analysis predicts how a structure behaves, while design works backward from performance requirements. It also discusses how FEA, design codes, engineering judgment, and AI fit into this perspective.

Is this a useful way to think about structural design, or just a different way of describing what engineers already do?

ASCE: https://doi.org/10.1061/JSDCCC.SCENG-2305

Free version (ResearchGate): https://www.researchgate.net/publication/399832621_Is_Structural_Design_an_Inverse_Problem

[u/Perfect-Mongoose-704]

Optimising beam sizes, and those sort of easy, repetitive calculations aren't really the hard part of SE, once you get past the graduate stage.

The hard part is choosing the least worst solution, given constraints around laws, design codes, available construction resources, schedule and budget. A lot of that isn't driven by technical decisions, but more the "politics" around the particular project.

AI and ML will definitely have a big impact on how the easy part of the job is done, but I'm less certain about how it'll effect the hard part.

[u/cougineer → u/Perfect-Mongoose-704]

This is my issue with AI and ML. Like I pull from old jobs but it’s “oh kinda like this, but not so also this job.” The projects I work on aren’t cookie cutter, have real limitations for cost and design. I get this guys paper maybe works for some building types but as I read it I go “this feels like a nothing burger written by a PHD.”

Also the devil is in the details, I have to iterate and change based on stuff that isn’t explicitly modeled but rather seen and transcribed into a model form. This is how I struggle seeing how this gets mixed into an AI/ML workflow

[u/Perfect-Mongoose-704 → u/cougineer]

Yeah. For me it's also stuff like "steel or concrete, which suits the contractor better".

OTOH, the other day I had copilot throw together some design spreadsheets, just to see how it would go. What it did was fine, and frankly better formatted than my own. Definitely at grad level quality.

Which is going to be the problem. I was able to check those spreadsheets as I had enough experience. They weren't actually perfect, I had to iterate a couple of times to get what I wanted. But putting together that sort of design tool was one way grads gained knowledge. We're going to have to work out how to continue doing that as an industry.

[u/cougineer → u/Perfect-Mongoose-704]

100%. How do you table AI making them? I’ve had little luck myself… given it’s been a while, maybe they got better.

[u/Perfect-Mongoose-704 → u/cougineer]

I tried it first a year ago, and it was terrible. I tried it again recently, and it was much better. I didn't throw anything to hard at it, just as a test.

I basically prompted it with something like

"Develop an excel spreadsheet to design a simply supported beam to AS4100".

AS4100 as I'm in Australia. And it did. I did a few others as tests as well, and it was pretty good.

[u/Ov3rKoalafied → u/Perfect-Mongoose-704]

Professors should give students spreadsheets with errors and have them diagnose the errors. Review hand calcs and diagnose the problem with them. But just as a supplement- still need homework and tests to primarily be working thru problems by hand.

[u/Perfect-Mongoose-704 → u/Ov3rKoalafied]

The problem is, who's going to employ grads when LLMs and ML can do their job

[u/Ov3rKoalafied → u/Perfect-Mongoose-704]

Their job will change. I will train new engineers to review output rather than create the output. That's not even any different than how we normally do it - I don't make new grads design concrete cores by hand. I teach them how to use ETABS and over time how to sanity check ETABS' results.

[u/Perfect-Mongoose-704 → u/Ov3rKoalafied]

I think the challenge is getting companies to employ grads, when this is going to be able to be done a lot more easily by LLMs rather than having to train a grad

[u/Ov3rKoalafied → u/Perfect-Mongoose-704]

AI and ML will make the easy part easier, which makes it easier to play the political aspect of dealing with changing scope and constraints. So many early budgets are set with very little structural information and I’ve already been able to provide framing layouts and preliminary designs faster and more accurately than in the past from ai assisted workflows. Once you get into the nitty gritty though you still very much need to rely on your own knowledge and expertise and AI has much less to offer. But I have more time to work on the nitty gritty thanks to ai helping with the other stuff.

[u/Minisohtan]

I think it's right, ignoring the SHM nonsense, right up until it suggests using AI to suggest sizes to optimize a design. That's not the way this will play out. The problem we face is that our software Sucks for optimization, or really running quickly in any sense. It suggests using traditional approaches to verify AI suggestions which leads us right back to shitty software.

AI will fix that. It has fixed it for me already. Get yourself an FEA package that can knock out a few thousand 3D FEA models in a day and you not need another layer with AI predicting beam sizes. I work routinely on complex bridges with influence surfaces for the live load. We have no problem rigouriusly optimizing our designs with traditional methods optimization methods.

Academia in the US is headed this way too. You won't be relevant if you can't knock out several thousand model parametric studies in a few weeks. Gone are the days of running two FEA models and generalizing it to a code equation.

Note, some people consider certain optimization approaches Machine learning. I'm not for simplicity here.

I like the inverse problem discussion.

[u/Intelligent-Read-785 → u/Minisohtan]

Back during the dream time I took a reinforced concrete design that included some structural analysis. The prof had quite a few experience in the design business mostly doing moments analysis. (Hell I can’t remember if that’s the.name of the process)He could look at a drawing of a multi-story building and explain how loads would be disturbed.

That may not be much of a skill but to a undergrad it was impressive. I wonder how of his understanding of structural behavior came from doing the calculations by hand. (Late
1960s) wonder if understanding of structures can by the way we crunch the numbers, by hand or machine v

[u/crvander]

Makes perfect sense to me. At risk of being burned at the stake (hopefully in effigy), these tools are coming whether we like it or not, and posing it this way is how we make sense of it and recognize where engineers and engineering tools fit together to solve problems. If we fail to define that and define our place in the design process, we instead let people who don't understand what we do day to day and the value we have try to replace us wholesale.

On a side forgetting about AI, machine learning, etc., this is just a good way of recognizing how the design process works. I've seen lots of junior engineers have it click that hey, we aren't going in one direction, we're always iterating, and you can reach an equally valid solution with 160 hours of thinking and tradeoffs as you can with 16 hours of an experienced engineer sketching out something that likely works and then verifying and optimizing it. I'm all for "different strokes" so to speak - some people understand the design process, iteration, etc., intuitively, but if thinking of it this way helps other people get there, that's great.

For what it's worth, this article is doing a bit of a rhetorical flourish because I think the answer to the title question is an easy "Yes" and it's posed more as a question to draw in people who don't know what the term "inverse problem" is as a starting point. Perfect archetype of the somewhat vaguely defined (but not without value) "thought leadership" trend.