Performance Evaluation of TMD under Typhoon Using System Identification and Inverse Wind Load Estimation

Abstract

The typhoon behavior and performance of a tuned mass damper (TMD) are presented based on the system identification and the inverse modal wind load estimation. The TMD was installed on a 39‐story, 184.6‐m steel building located in Incheon, Korea with a monitoring system consisting of an anemometer, accelerometers, and internet‐based data logging system. On September 2, 2010, the building experienced the Kompasu Typhoon, in which the peak wind speed, measured by an anemometer installed on the roof floor, was 49.7 m/s. To analyze the behavior of the building during the typhoon, the dynamic properties of building and TMD are identified from the measured responses. The modal wind load is then inversely estimated from the TMD and building accelerations using a Kalman filter, and the vibration reduction performance of the TMD is evaluated. The analysis results show that the typhoon‐induced vibration was reduced significantly due to the installation of TMD.

Identifying the Modal Parameters of a Structure from Ambient Vibration Data via the Stationary Wavelet Packet

“…Capable of reflecting the dynamic characteristics of a structure, modal parameters identified from its measured dynamic responses can offer a valuable reference to efforts to update structural design models (García‐Palencia and Santini‐Bell, ; Lozano‐Galant et al., ) and perform vibration control (Adeli and Saleh, ; Kang et al, ), health monitoring (Yuen and Katafygiotis, ; Soyoz and Feng, ; Hu et al., ), and damage assessment (Jiang and Adeli, ; Osornio‐Rios et al, ) of a particular structure. Identification of modal parameters from dynamic responses can be carried out in either the frequency, time or time–frequency domains.…”

Data‐Driven Two‐Level Performance Evaluation of Eddy‐Current Tuned Mass Damper for Building Structures Using Shaking Table and Field Testing

“…where x i is the ith measured response of the monitored structure;x i is the predicted response from a particular set of physical parameter vector z; rms is the root-meansquare operator; and N is the total number of DOF of the mechanical model. In terms of the physical modeling, the widely used shear-type models in TMD studies (Cho et al, 2012;Kang et al, 2012;Amini et al, 2013) and the classical Rayleigh damping assumption with the damping matrix proportional to the mass and stiffness matrices are adopted and can be calculated from two priorspecified damping ratios. Although there are different forms, including viscous and friction damping in reality, the Rayleigh damping with the description of damping ratios may be one of the most feasible choices of equivalent modeling of the physically complex energy dissipation phenomenon, which has been widely used in structural dynamics and analogous data-driven studies.…”

3D displacement measurement model for health monitoring of structures using a motion capture system

“…Accurate assessment of safety, however, is difficult, due to the analytical limitation and the fact that numerous assumptions must be made in the assessment process, considering the inherent uncertainties of large and complex civil structures. In this respect, in recent years many researchers have developed parametric system identification methods to estimate the structural parameters or non-parametric methods to estimate the structural response directly to be used in the analysis of the behavior of complex structures and determine their state of damage (Jiang and Adeli 2005;Adeli and Jiang 2006;Schoefs et al 2011;Marano et al 2011;Jafarkhani and Masri 2011;Sirca and Adeli 2012;Kang et al 2012;Hazra 2012;Yan and Ren 2012;Cho et al 2012;Fuggini et al 2013;Su et al, 2014). In addition, serviceability assessments using acceleration data require analysis of frequency and amplitude after measurements are completed making it difficult for the engineer to make a decision intuitively at the time of measurement.…”