CPE TPMS

CPE TPMS is a browser-based screening tool for metal additive manufacturing that helps engineers weigh triply periodic minimal surface lattice designs before they commit to a full simulation. TPMS lattices are the smooth, repeating internal structures used to make parts lighter, more porous, or tuned to a target stiffness, and choosing the right one usually means slow FEA or CFD runs. This tool sits earlier in the process, giving a fast first read on which lattice and material combinations are even worth modeling in detail. The goal is to spend simulation time only on candidates that already look plausible, rather than meshing and solving every idea an engineer might sketch.

The starting point is a plain-language description of the part. An engineer might type something like a titanium cylinder 50 millimeters across and 100 long that needs at least 70 percent porosity and 5 percent of the bulk material's stiffness, and the tool turns that sentence into geometry and screening parameters. The parsing is done by a deterministic phrase parser rather than a large language model, and it shows exactly how it read the request before returning anything, so there's no guessing about what assumptions went into the numbers. That transparency is a deliberate design choice for engineers who need to trust a result.

From that input it ranks seven lattice families, namely Gyroid, Schwarz-P, Schwarz-D, Diamond, IWP, Lidinoid, and Neovius, against the target. It works across thirteen laser powder bed fusion metals, checking each candidate's cell size and wall thickness against the feature limits of the chosen material so a suggested design is actually printable rather than just mathematically valid. The scoring returns in milliseconds because it leans on closed-form math instead of meshing and solving a model for every option. Each family behaves differently under load, so ranking them side by side is more useful than picking a favorite out of habit.

The estimates come from Gibson-Ashby power-law relations, the standard closed-form way to link a lattice's relative density to its effective stiffness. The tool uses those relations to work out how much solid material a target stiffness would need, then reports solid volume percentage, porosity, and rough cell size and wall thickness. When a request can't physically be satisfied, for instance very high stiffness paired with very high porosity, it says a tradeoff is required instead of handing back a false green light, which is the kind of honesty that early-stage screening actually needs. Reporting the tradeoff plainly means an engineer learns early that two targets are fighting each other, instead of discovering it after a long solve.

There are three ways to work with it. A describe-your-part tab handles the plain-language queries, a 3D playground lets you push topology, density, and material around and watch the estimated properties update live, and an analysis tab exposes direct JSON input for finer control along with API access. The audience is mechanical and additive-manufacturing engineers doing early concept work, the stage where you're narrowing a field of candidates rather than validating a final design that's already close to production. The JSON and API surface also makes it possible to script a batch of screenings rather than running each one by hand in the interface.

The team is clear about what the tool is not. It doesn't replace final verification for safety-critical parts, and it explicitly says it doesn't capture as-built defects, anisotropy, residual stress, fatigue, fracture, contact, complex heat flow, or resolved fluid flow. What it does well is triage. It compares early candidates quickly, catches incompatible targets before they waste hours of simulation, and produces a reproducible starting point that a full FEA study can pick up from later. Treated that way, it narrows the field so the expensive tools only run on designs that are worth the compute.

Access is a free public beta with no signup, running fully in the browser as a hosted app. The team describes it as a working beta rather than a finished product, so the sensible way to treat it is as a fast screening and sanity-check layer that sits in front of the heavier simulation tools, not as a replacement for them. For engineers who spend real time setting up FEA studies, a millisecond first pass that rules out the impossible combinations can save a lot of wasted modeling before the serious analysis even begins. The lack of a signup wall makes it easy to try a few queries and see whether the screening lines up with your own intuition before relying on it.