Uncertainty Analysis And Performance Assessment Of RC Frame Structures Based On Inspection Data And Monitoring Data

Infrastructure is the pillar of the national economy and social development.To guarantee the safety and functionality of structures,it’s of vital importance to assess the structures’ condition based on inspection data and monitoring data.In this context,a structural performance assessment frame based on inspection data and monitoring data is studied.Crack is the most representative inspection data,and a mechanics-based model is proposed to estimate the stiffness of RC beam/column with cracks.Then macro-level beam-column elements are employed to simulate the cracked structures by modifying the property of concrete based on the loss of stiffness.Five experimental beams are selected for validation.The results indicate that the stiffness-estimation model and proposed finite element method can describe the stiffness loss due to cracks accurately,and the capacity is also well simulated.The effectiveness of the stiffness-estimation model and proposed finite element method is proved,and the performance of cracked structures can be assessed based on it.For monitoring data,the Unscented Kalman Filter（UKF）,a method based on Bayesian theory,is employed to identify the structural state parameters.The corrosion process is selected as representative of the degradation processes.The simulation method for corroded structures is introduced,and a method based on UKF and monitoring data is proposed to estimate the corrosion degree and/or other structural state parameters.Two numerical cases,namely,three experimental beams and an RC frame finite element model,are employed for validation.The result indicated that the proposed method can accurately identify the corrosion degree and/or other structural state parameters based on monitoring data,even though noise exists,and the use of a fusion of different monitoring data can obtain a better performance.Based on the aforementioned method,a technique for establishing finite element models based on a fusion of inspection data and monitoring data is proposed.The technique involves two stages:（1）identify and update structural parameters in a macro level by using monitoring data;（2）identify and update structural parameters in local areas by using inspection data.To prove the effectiveness of the method,an RC frame structure experiment is conducted,which consists of two stages: a static lateral load stage and a quasi-static stage.The aim of the first stage is to produce some damage,and by using the inspection data and monitoring data in this stage,a finite element model that can reflect the damage state of the RC frame is established.The aim of the second stage is to validate the finite element model.The results show that compared with the initial finite element model,the finite element model based on a fusion of inspection and monitoring data can better describe the behavior and response of the structure,which indicates that the proposed method is effective.However,only a deterministic finite model is not sufficient for structural reliability assessment.Monte-Carlo method is the most popular technique to do structural probabilistic analysis and reliability assessment,but it has a considerable computational burden.A structural probabilistic analysis and reliability assessment frame based on the probability density evolution method（PDEM）is employed to solve this problem,in which the probability density function and probability distribution function of the structural response can be obtained while the calculation cost is reduced.By combining the PDEM-based reliability assessment method with the finite element simulation method that fused inspection and monitoring data,a time-dependent reliability assessment and performance prediction framework based on a fusion of inspection and monitoring data is proposed.Then the proposed frame is validated through an RC frame numerical example.The results indicate that the proposed frame works well;corrosion shows a significant influence on structural performance,and the structural reliability structure decreases gradually as time goes by.