Model-Selection Uncertainty Quantifications in HFFB Dynamic Analyses of a Complex Tall Building

Abstract

The high-frequency force balance (HFFB) technique is widely adopted for the assessment of wind loads acting on a tall building because of its simplicity and versatility. Although a number of HFFB-based analysis methods have been proposed to predict wind-induced dynamic responses of a tall building, these methods or models have mostly been developed based on various assumptions, which introduce different levels of inherent uncertainties and lead to a practical problem of method and model selections among available HFFB-based methods. It is necessary to quantify uncertainties in selecting the most robust and reliable model to carry out wind-induced response analysis with minimum uncertainties. The novel contribution of this paper is to establish a probabilistic framework for quantifying the model-selection uncertainty and weighting up the superiority among the candidate HFFB-based analysis models. A practical complex tall building is employed to demonstrate the proposed technique of uncertainty quantification in HFFB-based analysis for predicting wind-induced responses. Furthermore, the synchronous multipressure sensing system (SMPSS) test has been conducted in the wind tunnel to provide the benchmark results of the wind loads and a virtual set of HFFB base reactions obtained through integration of the measured pressure field.