Beyond Parametric: Explorable Simulation for Real Design Iterations
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 commercial experts who have currently raised €13m.
This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com (https://www.designforam.com?utm_medium=podcast&utm_campaign=CTA_1)
11 May 2026
Design For Real World Engineering: Integrating Uncertainty Into Product Assessment - Greg Grigoriadis - Metisec
Deterministic engineering analysis assigns fixed values to loading conditions, geometry, and material properties. The approach is tractable, but it forces a choice between conservative overdesign and exposure to failure modes that fall outside assumed limits. Neither outcome is satisfying.
Greg Grigoriadis of Metisec (https://www.metisec.co.uk/) describes a design toolkit that replaces fixed inputs with statistical distributions and runs Monte Carlo simulations across the resulting parameter space. The output is a probabilistic picture of performance: failure probabilities, sensitivity rankings, and the specific conditions that actually drive risk.
A sensor mounting bracket for a smart wearable serves as the test case. Traditional optimization cut bracket weight by 30%. Probabilistic analysis revealed the design had been tuned to an improbable drop event and still carried unresolved thermal failure risk. Incorporating that information allowed the team to re-optimize and achieve a 50% weight reduction at a demonstrably low failure probability.
Greg is an engineering consultant specializing in consumer electronics, digital twin technologies, and advanced simulation workflows. His practice combines physics-based modeling with data-driven methods across finite element analysis, predictive maintenance, and automated computation pipelines.
Presented at CDFAM Barcelona 2026. Learn more at cdfam.com.
This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com (https://www.designforam.com?utm_medium=podcast&utm_campaign=CTA_1)
4 May 2026
SEAT | Digitizing Body-in-White Development with MAS Synera
Body-in-White development sits at the intersection of structural performance, manufacturability, and schedule pressure — and traditional workflows are increasingly strained by the pace of platform proliferation and regulatory demands. This episode examines how SEAT/CUPRA is modernizing BIW development through Synera’s Multi-Agent System (MAS), connecting CAD, CAE, and manufacturing processes within a unified automation framework to accelerate iteration and improve engineering traceability.
Tilman Steininger, Customer Success Manager for Agentic Engineering at Synera, and Juan De Dios Escribano Felguera, Team Lead for Body-in-White and Corrosion Development at SEAT/CUPRA, present their collaborative work digitizing structural development workflows across the full BIW development cycle. Recorded at CDFAM Barcelona 2026.
About CDFAM
The CDFAM Computational Design Symposium is a global conference series bringing together researchers, engineers, and software developers working at the intersection of computational design, AI and machine learning for engineering and architecture. The program spans computational geometry, generative design, topology optimization, simulation-driven workflows, and advanced manufacturing across scales from architected materials to architectural systems. CDFAM events are held worldwide.
cdfam.com
This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com (https://www.designforam.com?utm_medium=podcast&utm_campaign=CTA_1)
Who has been a guest on CDFAM Computational Design Symposium
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Sergey Pigach
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Austin Mitchell
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