Statistical extremes and peak factors in wind-induced vibration of tall buildings

In the structural design of tall buildings, peak factors have been widely used to predict mean extreme responses of tall buildings under wind excitations. Vanmarcke’s peak factor is directly related to an explicit measure of structural reliability against a Gaussian response process. We review the use of this factor for time-variant reliability design by comparing it to the conventional Davenport’s peak factor. Based on the asymptotic theory of statistical extremes, a new closed-form peak factor, the so-called Gamma peak factor, can be obtained for a non-Gaussian resultant response characterized by a Rayleigh distribution process. Using the Gamma peak factor, a combined peak factor method was developed for predicting the expected maximum resultant responses of a building undergoing lateral-torsional vibration. The effects of the standard deviation ratio of two sway components and the inter-component correlation on the evaluation of peak resultant response were also investigated. Utilizing wind tunnel data derived from synchronous multi-pressure measurements, we carried out a wind-induced time history response analysis of the Commonwealth Advisory Aeronautical Research Council (CAARC) standard tall building to validate the applicability of the Gamma peak factor to the prediction of the peak resultant acceleration. Results from the building example indicated that the use of the Gamma peak factor enables accurate predictions to be made of the mean extreme resultant acceleration responses for dynamic serviceability performance design of modern tall buildings.

[1]  Kenny C. S Kwok,et al.  Cross Correlations of Modal Responses of Tall Buildings in Wind-Induced Lateral-Torsional Motion , 2009 .

[2]  Xinzhong Chen,et al.  Evaluation of peak resultant response for wind-excited tall buildings , 2009 .

[3]  Mark E. J. Newman,et al.  Power-Law Distributions in Empirical Data , 2007, SIAM Rev..

[4]  Muhammad R. Hajj,et al.  Theoretically estimated peak wind loads , 2007 .

[5]  J. Holmes,et al.  Probability distributions of extreme pressure coefficients , 2003 .

[6]  Jack E. Cermak,et al.  Wind-tunnel development and trends in applications to civil engineering , 2003 .

[7]  Fahim Sadek,et al.  Peak Non-Gaussian Wind Effects for Database-Assisted Low-Rise Building Design , 2002 .

[8]  Sun Bing-nan,et al.  Wind-induced stochastic response of controlled tall buildings by complex-mode analysis , 2000 .

[9]  Luo Shunlong,et al.  Probability distribution of , 1997 .

[10]  N. Isyumov,et al.  Performance of a tall building under wind action , 1992 .

[11]  W. H. Melbourne,et al.  Accelerations and comfort criteria for buildings undergoing complex motions , 1992 .

[12]  S. Winterstein.  Nonlinear Vibration Models for Extremes and Fatigue , 1988 .

[13]  A. Kareem.  Wind effects on structures: a probabilistic viewpoint , 1987 .

[14]  W. H. Melbourne,et al.  Comparison of measurements on the CAARC standard tall building model in simulated model wind flows , 1980 .

[15]  E. Vanmarcke.  On the Distribution of the First-Passage Time for Normal Stationary Random Processes , 1975 .

[16]  E. Vanmarcke.  Properties of Spectral Moments with Applications to Random Vibration , 1972 .

[17]  A G Davenport,et al.  NOTE ON THE DISTRIBUTION OF THE LARGEST VALUE OF A RANDOM FUNCTION WITH APPLICATION TO GUST LOADING. , 1964 .

[18]  Su Shengchung,et al.  Full-scale measurements and analysis of wind-induced response of Taipei 101 Tower , 2010 .

[19]  Kenny C. S Kwok,et al.  A peak factor for predicting non-Gaussian peak resultant response of wind-excited tall buildings , 2009 .

[20]  Armen Der Kiureghian,et al.  TAIL EQUIVALENT LINEARIZATION METHOD FOR NONLINEAR RANDOM VIBRATION , 2007 .

[21]  van Gjw Gerard Bussel,et al.  Reliability-based design methods to determine the extreme response distribution of offshore wind turbines , 2003 .

[22]  Ahsan Kareem,et al.  Analysis and simulation tools for wind engineering , 1997 .