Hybrid Physics and NN-Based Runtime Assurance for Integrated Vehicle Health Management

This innovation integrates a hybrid 6DoF-EoM physics-based and neural network-based RTA monitor as part of an advanced IVHM system onboard high-performance computing avionics of aircraft, UAVs, and autonomous flight systems to enable real-time fault detection, anomaly prediction, and adaptive protection. The system conducts live cross-verification of sensor and actuator behavior against physics-consistent predictions and data-driven estimates. This enables detection of anomalies such as sensor drift, loss of control, actuator faults, and approach to flight envelope boundaries. This is critical for NASA and Armstrong because it advances safe testing and operation of new autonomous or envelope-pushing aircraft, directly reducing risk during experimental flights and enabling smarter fault mitigation than current systems.

This work could transform how NASA and industry handle onboard vehicle health, enabling more aggressive testing of advanced control laws, reducing heavy physical redundancy, and certifying autonomous systems to operate in complex airspace. Primary stakeholders are NASA AFRC flight test and controls teams, specialized sensor technology developers, ARMD autonomy and safety researchers, DoD's UAV and hypersonic vehicle developers, and regulatory bodies like the FAA that depend on provable onboard safety measures.

This is a mature technology (TRL 7+) — the realistic path in is usually NASA's Technology Transfer Program: licensing an existing NASA patent, or a Space Act Agreement to use NASA facilities/expertise directly. NASA also runs a startup licensing program with no upfront fee for companies formed to commercialize a specific NASA technology.

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