Abstract
Wind tunnel model studies were carried out to determine the wind load distribution on tributary areas near the gable-end of large, low-rise buildings with high pitch planar and curved roof shapes. Background pressure fluctuations on each tributary area are described by a series of uncorrelated modes given by the eigenvectors of the force covariance matrix. Analysis of eigenvalues shows that the dominant first mode contributes around 40% to the fluctuating pressures, and the eigenvector mode-shape generally follows the mean pressure distribution. The first mode contributes significantly to the fluctuating load effect, when its influence line is similar to the mode-shape. For such cases, the effective static pressure distribution closely follows the mean pressure distribution on the tributary area, and the quasi-static method would provide a good estimate of peak load effects.
Abstract
This paper presents a methodology for spatial extrapolation of wind-induced pressure time series from a corner bay to roof locations on a low building away from the corner through the application of proper orthogonal decomposition (POD). The approach is based on the concept that pressure time series in the far field can be approximated as a linear combination of a series of modes and principal coordinates, where the modes are extracted from the full roof pressure field of an aerodynamically similar building and the principal coordinates are calculated from data at the leading corner bay only. The reliability of the extrapolation for uplift time series in nine bays for a cornering wind direction was examined. It is shown that POD can extrapolate reasonably accurately to bays near the leading corner, given the first three modes, but the extrapolation degrades further from the corner bay as the spatial correlations decrease.
Key Words
proper orthogonal decomposition; extrapolation; pressure time series; low-rise buildings; database-assisted design.
Address
Alan G. Davenport Wind Engineering Group, Boundary Layer Wind Tunnel Laboratory, The University of Western Ontario, London, Ontario, N6A 5B9, Canada
Abstract
The design of truss type sign support structures is based on the guidelines provided by the American Association of State Highway and Transportation Officials Standard Specifications for Highway Signs, Luminaries and Traffic Signals and the American Institute of Steel Construction Design Specifications. Using these specifications, the column design strength is normally determined using the effective length approach. This approach does not always accurately address all issues associated with frame stability, including the actual end conditions of the individual members, variations of the loads in the members, and the resulting sidesway buckling for truss type sign support structures. This paper provides insight into the problems with the simplified design approach for determining the effective lengths and discusses different approaches for overcoming these simplifications. A system buckling approach, also known as a rational buckling analysis, is used in this study to determine improved predictions for design strength of truss type sign support structures.
Address
Jun Yang; Department of Civil & Environmental Engineering, University of Connecticut, Storrs, CT 06268, USArnMichael P. Culmo; CME Associates, Woodstock, CT 06281, USArnJohn T. DeWolf; Department of Civil & Environmental Engineering, University of Connecticut, CT 06268, USA
Abstract
In common approaches, bridge dynamics under wind action is analyzed by modeling the interaction between fluid and structure by means of transient wind loads acting over the structure itself. Amid various possible manners to describe such types of loads, a representation based on families of `indicial functions\' is adopted here. The aim is to investigate its flexibility to capture the main features of wind-bridge interaction. A set of coefficients is involved in indicial functions. The values that one may attribute to them suffer uncertainties coming from experimental errors affecting data. Here, the sensitivity of a 2-DOF schematic model to the variations of these coefficients is investigated at fixed values of dynamic derivatives and for various types of indicial functions. It is shown how parameter variations influence phase portraits.
Key Words
aeroelasticity; bridges; time-domain simulations; indicial functions.
Address
CRIACIV ( 1 ), Dipartimento di Ingegneria Civile, Universita degli Studi di Firenze, Firenze, Italy
Abstract
This paper presents a time domain approach for predicting buffeting response of long suspension bridges under skew winds. The buffeting forces on an oblique strip of the bridge deck in the mean wind direction are derived in terms of aerodynamic coefficients measured under skew winds and equivalent fluctuating wind velocities with aerodynamic impulse functions included. The time histories of equivalent fluctuating wind velocities and then buffeting forces along the bridge deck are simulated using the spectral representation method based on the Gaussian distribution assumption. The self-excited forces on an oblique strip of the bridge deck are represented by the convolution integrals involving aerodynamic impulse functions and structural motions. The aerodynamic impulse functions of self-excited forces are derived from experimentally measured flutter derivatives under skew winds using rational function approximations. The governing equation of motion of a long suspension bridge under skew winds is established using the finite element method and solved using the Newmark numerical method. The proposed time domain approach is finally applied to the Tsing Ma suspension bridge in Hong Kong. The computed buffeting responses of the bridge under skew winds during Typhoon Sam are compared with those obtained from the frequency domain approach and the field measurement. The comparisons are found satisfactory for the bridge response in the main span.
Key Words
long suspension bridge; skew winds; buffeting response; time domain; equivalent turbulent wind velocity; field measurement; Typhoon Sam; comparison.
Address
G. Liu and Y. L. Xu; Department of Civil and Structural Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, ChinarnL. D. Zhu; State Key Laboratory for Disaster Reduction in Civil Engineering and Department of Bridge Engineering, Tongji University, Shanghai 200092, China