Extreme value prediction of the vehicle-induced displacement of a bridge under random vehicle load

Abstract

To accurately predict the extreme value of the vehicle-induced displacement of a bridge under random vehicle load, the Monte Carlo random sampling method was used to establish a random traffic flow load model, which fully considered the randomness characteristics of vehicles crossing the bridge. On the basis of the extreme value prediction theory of the classical Rice formula, we proposed a prediction method for the vehicle-induced displacement extreme value of highway bridges. The results of engineering applications show that the classical Rice formula has a good fitting effect on the threshold crossing times of the vehicle-induced displacement limit of bridges. The prediction method for the extreme value of vehicle-induced displacement of bridges is effective, reliable, and convenient for application in engineering practice. The displacement threshold crossing rate of small- and medium-span bridges under random vehicle load mainly depends on the number of vehicles crossing the bridge and is less affected by the distance between these vehicles. The extreme value of the vehicle-induced displacement of the bridge increases with an increasing return period. The extreme value of vehicle-induced displacement and the failure probability of the first excess displacement of the side beam of a beam bridge are greater than those of other main beams.