Life-cycle cost and uncertainty analysis of high-performance control systems in wind-excited tall buildings

High-performance materials and modern construction techniques are contributing to the development of taller and more flexible buildings. These structures are characterized by higher periods and are thus more prone to wind-induced vibrations. Frequent wind events cause occupants’ discomfort and affect daily operations, while severe windstorms induce damage to structural and nonstructural elements. A solution to mitigate wind-induced vibrations is the deployment of high-performance control systems (HPCSs). HPCSs, including active, hybrid, and semi-active control strategies, are sophisticated vibration mitigation devices. They rely on adaptive rules to offer an improved mitigation capability relative to traditional passive dampers. Nevertheless, the implementation of HPCSs is still in its infancy. HPCSs are perceived as less reliable systems, as they are inherently subjected to unexpected mechanical and electrical events, such as the failure of an electrical or mechanical component. Moreover, the integration of HPCSs in the structural system entails additional costs, associated with installation and maintenance of damping devices, sensors, and computers. The broad objective of this dissertation is to promote the applicability of HPCSs, providing a financial tool to justify their utilization, and considering the uncertainties in the HPCS configuration. In order to reach this objective, a life-cycle cost analysis (LCCA) framework, embedded in a Performance-Based Design (PBD) procedure, is first proposed. The focus of this procedure is on wind-excited tall buildings equipped with motion control devices. Next, the LCCA procedure is further developed to consider the uncertainties in the HPCS configuration (e.g., sensor failure, material wear, power unavailability). Such analysis would result in a computationally demanding task due to the very large number of simulations required given the large number of HPCS uncertainties and the variability of the external load. The large number of permutations to be considered, combined with the long duration of typical wind load events (in the order of hours), yields a large computational cost that often makes the uncertainty analysis impractical. To alleviate this computational demand, several uncertainty quantification techniques are investigated and embedded in the LCCA. These uncertainty analysis techniques are based on deterministic scenarios, stochastic scenarios and surrogate models