Episode

Beyond Parametric: Explorable Simulation for Real Design Iterations

Podcast
CDFAM Computational Design Symposium
Published
Sep 4, 2026
Duration seconds
1198
Processing state
not_requested
Canonical source
https://www.designforam.com/p/beyond-parametric-explorable-simulation
Audio
https://api.substack.com/feed/podcast/214154460/fa015e2ea0640bbd038510afed01b8b6.mp3
JSON
/v1/public/podcasts/cdfam-computational-design-symposium-7077587/episodes/beyond-parametric-explorable-simulation-for-real-design-iterations
Markdown
/podcast/cdfam-computational-design-symposium-7077587/beyond-parametric-explorable-simulation-for-real-design-iterations.md

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Summary

Beyond Parametric: Explorable Simulation for Real Design Iterations Presentation Abstract Design space exploration promises engineers the ability to evaluate thousands of variants in hours. The prerequisite—rarely discussed—is building a parametric geometry model that won’t break. This front-loaded investment assumes you know your design space before exploring it. Real engineering iteration isn’t parametric. Design changes are structural and topological: fundamentally different geometries evaluated against the same performance criteria. Setup time, not simulation time, is the real bottleneck in enabling simulation-driven exploration for real engineering teams. At Generative Engineering, this is what we are addressing. We enable explorable simulations that work with both parametric exploration and novel designs. We will demonstrate how this is unlocked by using existing simulation data inside engineering organisations to train geometry preparation models rather than physics surrogates. This lets the messy, collaborative, real design iterations be simulated with zero setup cost. But the same principle extends further: if a model understands what makes geometry simulation-ready for a given analysis, it can generate that geometry directly. We’ll show work on closing this loop—from a sketch or annotation on a previous design to simulation-ready geometry, collapsing the traditional boundary between design intent and engineering validation. Speaker Bio Laurence Cook is Co-Founder and Chief Product Officer at Generative Engineering. After academic work at MIT, Stanford, and Cambridge, Laurence brought his computational engineering to the commercial industry and is now leading the initial commercial product of Generative Engineering. A 20 strong team of computational and commer…