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A wind and structural health monitoring system (WASHMS) was installed in the Tsing Ma suspension bridge in Hong Kong in 1997. On September 16, 1999, Typhoon York, which was the strongest typhoon since 1983 and the typhoon of the longest duration on record, crossed over Hong Kong. All vehicles, except trains, were prohibited from running on the bridge for 2.5 h. This event provided a distinctive opportunity to examine the existing analytical models for predicting dynamic response of long suspension bridges to high winds and running trains. The field measurement data recorded by the WASHMS during this event were therefore analyzed and the four particular cases were identified and discussed in this paper. The four particular cases identified included: (1) the bridge without any vehicles; (2) the bridge with one train; (3) the bridge with two trains running in opposite directions; and (4) the bridge with three running trains. The mean wind speed was almost perpendicular to the bridge alignment in the four cases to facilitate the comparison with analytical results. For each case, wind characteristics, bridge acceleration responses, and bridge displacement responses were analyzed using the measurement data from anemometers, accelerometers, and level sensing systems, respectively. The number of trains running on the bridge, train speed, and train location were also identified using the measurement data from strain gauges. The measurement results clearly demonstrated the dynamic behavior of the bridge with running trains during high winds. The measurement results obtained will also be used to verify the analytical model developed by the authors in the companion paper. [ABSTRACT FROM AUTHOR]

The field measurement results of the Tsing Ma suspension bridge under cross winds and running trains during Typhoon York have been presented in Part I of this study. The field measurement results are used in this paper (Paper II) to verify, to some extent, the finite element based framework developed by the writers in the time domain for predicting dynamic response of coupled train and bridge systems in cross winds. In this regard, a three-dimensional finite element model is used to model the Tsing Ma suspension bridge. Wind forces acting on the bridge are generated in the time domain using a fast spectral representation method and based on the field measurement results and wind tunnel test results. Each coach in a train running on the bridge is modeled by a 27 degree-of-freedom dynamic system. The dynamic interaction between the bridge and the train is realized through the contact forces between the wheels and the track. Track irregularity is simulated using a high-order multivariate autoregressive model, whereas wheel hunting is assumed to be a sinusoidal function with a random phase. The acceleration and displacement responses of the bridge under cross winds and running trains are computed and compared with the responses measured from the field for four cases. The comparison is found to be satisfactory in general. The dynamic response and performance of trains on the bridge is also computed and evaluated. The proposed framework is found to be feasible and practical. [ABSTRACT FROM AUTHOR]

This paper presents work on validating the dynamic wind load predicted by a wind tunnel model with the values identified from full-scale field vibration data of a super-tall building in Hong Kong. Dynamic wind load in this work refers to the power spectral density (PSD) of the modal force near the natural frequency of a particular mode of the building, in the context of random vibration with stationary loading and response. This quantity reflects the turbulence characteristics integrated over the building body and is of importance in wind engineering design. This study presents a method to predict the modal PSD of wind load of the first two translational modes of a tall building. The method combines wind tunnel test information and mean wind data available in the free field; the latter taken to be at the Waglan Island station maintained by the Hong Kong Observatory. On the full-scale side, although the modal PSD is not directly observable, it is identified from field vibration data measured at the building top during strong wind events. A Bayesian modal identification method is used for determining the most probable value and the uncertainty of the modal parameters including the natural frequency, damping ratio, and the modal PSD. A number of recent strong wind events are analyzed. Reasonable agreement is observed between the wind tunnel model predictions and the values identified from field data. Factors that can potentially lead to discrepancy are discussed. As the same random vibration modeling consistent with conventional wind engineering design has been used in the wind tunnel prediction model and field identification model, the results are directly transferable among these three disciplines. [ABSTRACT FROM AUTHOR]