Correction of coupled aerodynamic loads in high-frequency force-balance testing using a Bayesian approach

<p dir="ltr">High-frequency force-balance testing is one of the most practical approaches for evaluating wind loads and wind-induced responses on high-rise buildings in wind tunnels. However, the method is susceptible to measurement bias caused by resonant amplification and modal coupling between the balance and the structural model. Traditional correction methods partly mitigate resonant amplification but remain limited under modal coupling, particularly in cases of closely spaced modes. This study presents a physically grounded correction framework based on Bayesian operational modal analysis, which incorporates the coupled dynamic characteristics of the balance model system (BMS) into a Bayesian inference scheme, enabling statistically consistent and physically interpretable identification of its modal characteristics. By leveraging the identified modal parameters of the BMS, the method decouples aerodynamic loads, suppresses dynamic amplification, and reconstructs bias-reduced aerodynamic load spectra. Numerical simulations demonstrate the robustness of the method under varying modal proximity and coupling, while wind-tunnel experiments on a supertall building model further validate its effectiveness. The results highlight the potential of the proposed framework to improve aerodynamic-load correction and structural-response prediction in wind-tunnel testing</p>