An Innovative Derivation Methodology to Accurately Predict Rotor Head Loads Generated over Various Rotorcraft Flight Regimes

We proposes to develop a Surrogate Model Assisted Rotor Load Derivation (SMARLD) system that features an innovative combination of coupled physics-based rotor/tail-rotor/fuselage simulation, load correction using fuselage sensor measurements, surrogate (data-driven) modeling, and uncertainty quantification to achieve improved structural modeling and fatigue life calculation. The technology is based on the principle that fuselage sensor measurement data enable accurate derivations of main rotor blade loads in rotating frame via a carefully established inverse problem. In Phase I we will conduct comprehensive simulations using MBDyn multi-body dynamics code to capture rotor loads, hub forces, and fuselage responses characteristics under hover and steady state flight conditions. Then, fuselage measurement data will be used to correct rotor blade load predictions in order to build a validated database. Along with available flight test data, a mapping between the rotating frame rotor blade loads and fuselage responses will be established via surrogate models. Such surrogate models will significantly improve the prediction efficiency which allows us carry out uncertainty quantification in the inference phase. Finally, the proposed SMARLD system will be demonstrated to determine main rotor blade loads which including the amplitude, phase, and frequency content and validate by flight test data under hover flight condition.