Prediction of UH-60A Blade Loads: Insight on Load Confluence Algorithm

Accurate predictions of the aeroelastic response of a rotorcraft are essential to minimize weight and estimate the fatigue life of rotary-wing aircraft components. Aeroelastic analyses are characterized by strong couplings between the aerodynamic loads and the structural response and are very time-consuming, in particular when computational-fluid-dynamics predictions of airloads are coupled with computational-structural-dynamics models. Simple aerodynamic models do not predict the response of the system with sufficient accuracy. A novel combined numerical and experimental algorithm, the load confluence algorithm, is developed to iteratively correct the numerical model of the external loads from minimal experimental data to best represent the experimental response. Aerodynamic loads are modeled with a simple approach, such as the lifting-line theory. The proposed algorithm uses the measured strains as inputs to a strain mapping algorithm, which then predicts force and moment corrections using a modal approach. These corrections are added to the lifting-line forces and moments to obtain a close correlation between measured and computed strains. This paper analyzes the influence of user-defined parameters on the convergence of the proposed approach. Results for three different steady forward-flight conditions of the UH-60A Black Hawk helicopter demonstrate the ability of the algorithm to accurately predict the flapwise, edgewise, and torsional internal moments along the blade with an accuracy that is comparable with detailed computational-fluid-dynamics analyses with a much reduced computational cost.