Tall Buildings and Damping: A Concept-Based Data-Driven Model

Abstract

Modern tall buildings are characterized by their slenderness and sensitivity to resonant wind effects. This is especially true considering the acceleration-based motion perception criteria under which they must be designed. In light of the significance of the resonant response, damping plays an important role in the design of tall buildings. Unfortunately, unlike other mechanical characteristics of structures, damping is far more difficult to estimate. This is due to the inherent complexity and high number of mechanisms responsible for damping. For this reason, the experimental determination of damping levels for tall buildings from full-scale data collected during monitoring programs has obtained a tremendous amount of interest over the past years. This paper firstly reviews the predictive damping models that are available in the literature highlighting their merits and shortcomings in light of the extensive experimental damping data collected over the past few years. A novel amplitude-dependent data-driven model is then proposed based on a fully probabilistic description of the mechanisms that are hypothesized to generate the majority of damping in tall buildings. Finally, the proposed model is calibrated to a number of specific buildings demonstrating its robustness.