Research On Maintenance Cost Optimization Of Bridge Pier Based On Probabilistic Models

Traditional seismic design usually does not take the influence ofchloride-induced corrosion into consideration. However, the seismic capacity ofthe reinforced concrete bridge gradually decreases with the increase of service life,which will lead to the high cost of maintenance. Introducing the life-cycle theoryinto the construction and maintenance has attracted great attentions of theresearchers. The life-cycle theory mainly deals with the relation between structureperformance and the total cost during the whole life cycle. To minimize themaintenance cost of the reinforced concrete bridge is the key to optimize thestructure safety and cost.This paper investigates the dynamic reliability and status indicators of thebridge pier during the service period based on the Monte Carlo method. The mainresearch content includes:(1)Based on the Fick's second law, the initial degradation time of thereinforced rebar is analyzed by using Monte Carlo method combing with thechloride ion diffusion model. A probability distribution model of the largestearthquake effect whose designed working life is100years is established. Thevariation of the time-varying reliability index of the bridge pier is simulated byanalyzing the dynamic resisting capacity and the maximum earthquake effect.(2)A high-order nonlinear reliability degradation model, which contains twouniform random parameters, is established. Through comparing the exponentialmodel and linear model, the fitness the reliability index is analyzed. In order toquantitative analyze the appearance damage, a status indicators is introduced andthe quadratic nonlinear model is established. A transformation formula containstwo bridge pier indicators at any time is deduced based on the time andperformance maintenance strategy respectively combined with the performancedegradation model of bridge pier. The relevant formula used to calculate the costof maintenance is also established.(3)A Matlab programs is applied to analyze the variation and thecorresponding cost of the two indicators under single or combine maintenanceactivities. The analyzed results show that it is able to meet the requirements for thetwo indicators at the same time under combing maintenance activities comparedwith the situation under single. However, the maintenance cost is higher.(4)The multi-objective particle swarm optimization algorithm is used tooptimize the maintenance strategy related to the first maintenance time and the time interval. Finally, the combination maintenance strategy, which has theminimum cost, is chosen through comparing the cumulative cost of each combinemaintenance activity.