Physics as Infrastructure for the AI Era
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CDFAM Computational Design Symposium — Washington DC 2026
Rik Baruah · Intact Solutions
AI is reshaping engineering as it drives demand for surrogate models, large design studies, and agentic workflows that require automated simulation loops at scale. These pipelines collide with two realities: geometric representation is fragmented throughout the hardware lifecycle (from CAD to point clouds), and traditional FEA, reliant on conformal meshing and manual preprocessing, treats human intervention as a core requirement. This brittle paradigm resists automation.
Scaling simulation for the AI era is fundamentally an infrastructure problem. Using immersed grid methods, Intact natively ingests any geometry representation without preprocessing, exposing physics as an API-first callable function. We demonstrate how this architecture powers the emerging “engineering-as-code” stack through automated DOE pipelines and LLM orchestration via MCP across concept, manufacturing, and deployment.
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