We build digital twins for external flow problems — airfoils, blades, ducted geometries, rotor systems — where designers need to sweep thousands of geometries against multi-objective constraints, and operators need lift/drag predictions in real time.
Aerospace, energy (wind), automotive, UAM, drones, fans & blowers — anywhere external flow drives performance.
Four common deployments — each a domain where slow CFD blocks the design loop and pure ML can't be trusted by the regulator.
Sweep parametric airfoil families against lift-to-drag, stall margin, and noise objectives. The twin predicts pressure distributions and integrated forces across the Reynolds and angle-of-attack envelope.
Compressor & turbine blade aerodynamic surrogates. Loss prediction across off-design conditions, blade-row interaction modeling, and through-flow correction for preliminary design tools.
Drag prediction for vehicles, drones, and rotorcraft. Shape-aware surrogates that handle continuous geometric variation without remeshing — and stay physics-consistent on novel shapes.
Wind turbine blade aerodynamics, wake prediction, and farm-level yield modeling. Multifidelity: high-fidelity LES anchors the training; a fast PINN-derived surrogate runs in the control loop.
For continuous external flow, the governing equations are fully encodable. That's the regime where PINNs are most proven — and where they outperform pure data-driven ML.
The network is constrained to satisfy mass, momentum, and energy conservation — encoded directly into the loss. The result extrapolates to off-design conditions where pure data-driven models silently fail.
An aero deployment combines high-fidelity CFD, physics-AI acceleration, and a real-time twin layer.
A few representative deployments. More on the case studies page.
Wind-assisted propulsion, decarbonization compliance, fuel-saving decision intelligence.
/ 03 · Heat transferBattery packs, heat exchangers, process heating — wherever thermal management is mission-critical.
/ 04 · Process mfgElectrode mixing, coating, calendering — every step has a multiphysics signature.