Examination of experimental variability in HFFB testing of a tall building under multi-directional winds

Abstract

Examination of wind loading uncertainty is necessary for structural fragility analysis of tall buildings in the context of performance-based wind engineering. One of the sources of uncertainly is represented by random experimental error, which may occur during a standard test in wind tunnel, such as the high frequency force balance (HFFB) test. Few examples of systematic experimental error analysis are available. This study examines a series of experiments on a model of a standard benchmark building under simulated turbulent flow. HFFB experiments were conducted in the Northeastern University's small-scale wind tunnel. Three model equations are proposed to represent the power spectral density (PSD) functions of the above three forces in the frequency domain.Furthermore, effects of experimental errors are incorporated by allowing the parameters in each function to vary randomly. Variability is evaluated by considering the second-order statistical moments of the parameters (standard deviations and correlations). At last, this paper introduces a data-driven Monte-Carlo approach to reconstruct the generalized PSD of the wind loading through model equations. Experimental variability is accounted for by exploiting information on the probability distributions of the model parameters. Verification of the reconstructed PSD functions against experiments suggests that the Monte-Carlo approach can effectively generate synthetic PSD curves.