Load Spectrum Determination for Early-Stage Aircraft Design

Abstract In early-stage aircraft design, accurate load predictions are crucial for optimizing performance and mass. This paper presents a methodology for determining load spectra using Gaussian Process (GP) surrogate modeling, focusing on landing gear dynamics. In this study, uncertainties in design parameters and their impact on dynamic loads during landing are addressed. By employing a simplified landing gear model and dimension reduction techniques, the GP model predicts dynamic response of the landing gear under various conditions. The results highlight the importance of subsystem optimization to reduce peak loads and improve design robustness. This approach enables more informed decision-making in the preliminary design phase, avoids unnecessary conservatism in structural design. The findings demonstrate that incorporating uncertainty with respect to aircraft design choices can lead to realistic distributions of aircraft load ranges through the incorporation of subsystem optimization.