Stochastic Dynamic Response Analysis of a Steel-Framed Glass-Deck Pedestrian Bridge Considering Pedestrian-Load Randomness and Selected Structural-Parameter Uncertainties

This study investigates the stochastic vibration response of a laboratory steel-framed glass-deck pedestrian bridge subjected to random pedestrian loads and structural damping ratio uncertainty. A probabilistic pedestrian load model was established by considering walking frequency, body mass and step length as random variables. The probability density evolution method (PDEM) was then adopted to evaluate the time-varying probability density function of the midspan acceleration response. The dynamic responses under single-person walking, four-person simultaneous entry, and four-person interval walking conditions were first analyzed and compared with measured acceleration responses acquired from the laboratory test bridge. In addition, a single-pedestrian high-frequency walking load test with a target cadence of approximately 4.2 Hz was conducted to investigate the bridge response under near-resonant excitation. Subsequently, damping-ratio uncertainty was introduced together with pedestrian-load randomness to investigate the coupled influence of pedestrian excitation and structural damping on the stochastic response. The results show that the acceleration response under four-person group walking is higher and more probabilistically dispersed than that under single-person walking. When structural parameter uncertainties are considered, the peak midspan acceleration increases from 0.1978 m/s2 under pedestrian-load randomness alone to 0.2487 m/s2, corresponding to an increase of approximately 25.7%. The response mean and standard deviation predicted by PDEM agree well with those obtained from Monte Carlo simulation under the same numerical settings. Overall, the PDEM-based framework provides a probabilistic description of the transient bridge response and quantifies the influence of pedestrian-load randomness and structural damping uncertainty on response variability.