Vortic CFD builds machine learning models trained on high-fidelity CFD: predicting how a design will perform, working out where to place a sensor, controlling a system in real time, and automatically searching thousands of design variants. CFD generates the data. This is what gets built on top of it.
From sensor placement to full-vehicle aero, every study is scoped around a specific question a team is trying to answer.
Machine learning built around your specific system: predicting how a design will perform, working out where to put a sensor, or exploring a design space automatically.
Control systems that adjust in real time as conditions change, trained on simulation data instead of tuned by hand.
External flow analysis to understand drag, downforce, and balance across a full vehicle or individual components.
Underhood and duct-level airflow analysis to keep components in their operating window without paying unnecessary drag.
Simulation-backed validation of a design direction before it reaches manufacturing.
The machine learning capability, and the full-vehicle aero study it's built on.
