Spectral characterization of the stochastically simulated vehicle queue on bridges

Monte Carlo simulation in conjunction with Fourier transform based spectral windowing is used to model the live load on bridges. Vehicles are classified into a few groups and the probability distributions of axle weight and length associated with each group are estimated. The vehicle arriving at an instant is determined through Monte Carlo simulation, which uses a vehicle group density function derived from measurement data on the relative contribution of each group in total vehicles. The weight and length of the arriving vehicle is also simulated by Monte Carlo using the distribution function for the corresponding group. Vehicle arrivals are modeled by the Poisson distribution. The vehicle velocities are realized through spectral simulation based on decaying power spectra of the velocity time series. The simulations are performed for a sufficient time interval in several lanes, thus the ensemble sampling of load is obtained. Fourier transform based windowing is used to characterize the power spectra of mechanical load on the bridge. The study shows the white noise nature of the load spectral density, which is in agreement with the assumptions of previous investigators. Parametric sensitivity of the spectra is also performed and recommendations are made to include site-specific parameters in the model. Finally, applications are illustrated for frequency domain random vibration analysis of a simple model of bridge structures.