C.K. Wong

Full scale measurements of wind effects on tall buildings

This paper describes the results obtained from the measurements of wind effects on two tall buildings with 70-storeys and 30-storeys, respectively. The field data presented are wind velocity and acceleration response measured at the top of the tall buildings over the last two years. The damping characteristics which were obtained by using the random decrement technique are demonstrated and discussed.

Damping in buildings: its neural network model and AR model

The results of full scale measurements of damping as well as other researches on damping show that damping in buildings exhibits randomness and amplitude dependent behaviour in the case of tall buildings subjected to dynamic loading. In this paper, based on full scale measurements of damping in a tall building, a time series analysis method (TSA) is employed to obtain the relationship between damping and vibration amplitude. Then, two models of damping in a tall building, the artificial neural network (ANN) model and the auto-regressive (AR) model, are established by employing ANN and AR methods, and used to predict the damping values at high amplitude level, which are difficult to obtain from field measurements. In order to get high accuracy, a genetic algorithm strategy is employed to aid in training the ANN. Comparison analysis of the neural network model and the AR model of damping is made, and the results are presented and discussed.

Evaluation of wind effects on a supertall building based on full‐scale measurements

This paper describes the results obtained from the full-scale measurements of wind effects on a 70-storey building in Hong Kong. The building which has a height of approximately 370 m is the second tallest structure in Hong Kong. The field data such as wind speed, wind direction and wind-induced acceleration responses have been measured since 1995 including the close passage of two typhoons; typhoon Sally and typhoon Kent. Detailed analysis of the field data is conducted. The full-scale measurements are compared with the wind tunnel results obtained in the Boundary Layer Wind Tunnel Laboratory at Western Ontario University. The amplitude-dependent characteristics of damping and natural frequency that were obtained by using the random decrement technique are investigated. Copyright

Random damping in buildings and its AR model

Abstract The full-scale measurements of damping show that damping in buildings exhibits randomness. The randomness of damping is examined in this paper. The factors which govern damping contributions in buildings, at different vibration amplitude levels, are investigated based on the Jearys damping model [Earthquake Eng. Struct. Dyn. 14 (1996) 733–750]. It is found that, at a high amplitude level, damping in buildings is mainly dominated by random factors. In order to investigate the amplitude-dependent characteristics and randomness of structural damping, a time series analysis method (TSA) is employed to obtain the relationship between damping and vibrating amplitude. The AR (auto-regressive) models of damping in a building have been established and used to predict the damping values at high amplitude level, which are difficult to obtain from field measurements. The predicted data of damping show that damping values, at high amplitude, fluctuate around a plateau value described by Jearys damping model.