The plan and section are schematic extrusions of the solved elevation across a deck width — not a second optimization, just the same result shown the way a drawing set shows it. The point is the jump every engineer knows: a beautiful 2D optimum still has to become a 3D thing with width, connections, and a deck on top. That translation is exactly the gap the MIT work is trying to close.

The savings were never the news. Topology optimization has been cutting material by large fractions for decades. The problem is the part you already know in your bones: it spits out complex, spiderweb structures that even a capable engineer can't actually build — so the method got quarantined into 3D printing and research and basically never touched a real bridge. The paper's specific result isn't a headline savings percentage at all: it shows that the lowest-carbon design changes significantly once you force it to be buildable, and that giving the optimizer a lower-carbon material option helped by nearly 29% in one example and almost not at all in another. The savings the field already knew how to get (topology optimization can reach as much as 90% in some cases, per MIT's release) now arrive in a form you can actually construct — which is the real headline.

What's new: Schemmer (first author) and Carstensen (senior) moved constructability inside the optimizer, using a mixed-integer linear programming (MILP) formulation over discrete truss members. You constrain how many members meet at a joint, set how small the smallest part can get, work in multiple materials, and account for how each one carries load. The optimizer is no longer allowed to hand you something you can't build. The "minimum member size" knob on this bench is a loose stand-in for that idea — not the MILP itself.

This tool lets you feel that tradeoff instead of reading about it — and then it adds the part no optimizer does: the site that has to hold the thing.

Sources