Surrogate Modeling for CFD Applications
Surrogate modeling is an AI-driven approach that replaces expensive CFD simulations with fast, accurate predictive models. By learning from high-fidelity simulations, these models provide near-instant results, enabling engineers to optimize designs efficiently.
Key Benefits
✅ Faster Predictions: Get results in seconds instead of hours.
✅ Reduced Computational Cost: Avoid running expensive CFD simulations.
✅ Data-Driven Accuracy: Models trained on validated CFD results.
✅ Integration Ready: Works alongside existing engineering workflows.
AI On the Edge
Real-time recognition of a constantly changing scene based on video streaming requires high data bandwidth if performed in the cloud
Available Models
Aerodynamic Performance Predictors
(Lift, drag, and moment coefficients)
Flow Field Property Estimators
(Velocity and pressure distribution)
Unsteady Flow Predictors
(Transient wake behavior, vortex shedding)
Shape Optimization Surrogates
(Fast geometry-based predictions)
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