Physics AI for Aerospace Development
Predict and verify physical behavior in real time, from conceptual design through operations.
What We Deliver
A large physics model built on your data, and the factory that produces it.
Luminary enables you to build a large physics model grounded in real physics, trained on simulation, experimental, and operational data. A trained model enables any engineer, or an AI agent, to submit a geometry and flight condition and get a prediction of physical behavior in seconds, across aerodynamics, structures, thermal, and acoustics. No meshing. No PhD required to run it.
Producing that model is a production line, and Luminary's Physics AI Factory runs it end to end. GPU-native solvers generate training data at scale, automated pipelines train the model and validate it against evolving test suites, and each version is deployed into the tools your engineers already work in. Retraining runs as new simulation and test results land, so the model keeps pace with the program.
Predictions can be validated against high-fidelity simulation whenever it matters. The platform deploys in the cloud, your VPC, on-premise, or in an air-gapped, ITAR-secure environment, and every model your team builds stays yours: your data, your model, your IP.
Forward deployed engineers work alongside your team to scope the highest value use case, build the model, and integrate it into how you already design. And because the model keeps learning from new programs and in-service data, verification continues through years of operation, informing digital twins and predictive maintenance.
Proven on real aerospace programs.
You can take complete aircraft configurations and run them in a matter of minutes. It allows a level of confidence that was unprecedented before.
Gregor Veble Mikić, Chief Aerodynamicist, Joby Aviation
We spent a week trying to close up on a complex full-aircraft grid, but it kept crashing in NASA's GridTool. Within minutes, we were able to grid and run that solution in Luminary.
Buddy Sessoms, CPO, Piper Aircraft
By running our proprietary flight sciences on their platform, we're accelerating innovation and developing next-generation Physics-AI models across our design process.
Obi Ndu, Chief Information & Digital Officer, Otto Aviation
Challenges in Aerospace
Physical verification is the bottleneck, at every stage.
Verification Is Manual and Slow
Geometry, meshing, and solver setup can take hours to days per run, and the burden compounds as more runs are needed.
The Design Space Is Bigger Than Teams Can Afford to Test
Each simulation is compute intensive and bespoke to one geometry and one condition, so only a narrow set of options ever gets evaluated.
Multi-Physics Is Where It Breaks Down
Coupled problems, like thermal-structural or aeroelastic behavior, need two experts and two tools passing information back and forth by hand.
A Scarce Expert Gates the Whole Team
PhD-level specialists are required to set up and run traditional tools, so the rest of the organization waits on a handful of people.
Certification Demands Traceability, Not Just Speed
Safety-critical systems raise the bar for model trust, verification, and documentation well beyond what a faster tool alone can satisfy.
Verification Stops at the Factory Door
Once a system is in service, there is no continuous way to fuse operational data with physics and predict how it will behave as conditions change.
Why Luminary
Use Cases
Physics AI across the decisions that gate a program.
Physics AI applies well beyond aerodynamics: fluids, thermal, structures, dynamics, manufacturing, and system integration all gate a program somewhere along the way.
Concept Exploration & Inverse Design
Evaluate novel geometries and mission or cycle sizing at low cost, early, before committing to an architecture.
Guidance, Navigation & Control
Physics-informed models for closed-loop control that respect the vehicle's governing dynamics.
Aerodynamic Prediction & Design Optimization
Predict aerodynamic forces, moments, and full surface fields in seconds, and optimize across competing objectives such as drag, weight, and noise.
Thermal & Cooling Design
Model turbine cooling, environmental control systems, nacelle, and power electronics thermal behavior.
Structural Sizing, Loads & Margin Analysis
Size structures and analyze the loads envelope across a much larger part of the design space.
Aeroelasticity, Dynamics & Acoustics
Address flutter, rotordynamics, and community noise together, instead of one discipline at a time.
Test Campaign Optimization & Virtual Sensing
Plan test campaigns more efficiently and fill in what physical instrumentation cannot measure directly.
Durability, Fatigue & Life Prediction
Predict damage tolerance and service life to plan inspection and maintenance intervals with more confidence.
Certification Support & Model-Form Error Quantification
Quantify model error so conservatism is backed by numbers, not carried as unexplained margin.
Manufacturing & Process Physics
Model cure distortion, forming, casting, additive residual stress, and weld distortion before they become scrap on the shop floor.
Digital Twins & Virtual Twins
Combine simulation, test, and live operational data to track expected behavior and support in-service decisions.
Maintenance & Operational Intelligence
Fault detection, structural inspection, and trajectory prediction that extend Physics AI into sustainment.
Flight Simulation & Virtual Training
More realistic, more responsive simulators for pilot training and off-nominal scenario testing.
See It on Your Own Geometry.
Bring a real design problem. A Luminary engineer will show you what Physics AI looks like on it, not a demo.