BAYESIAN MODEL UPDATING BASED ON STRUCTURAL RELIABILITY METHOD: CASE STUDY FOR CHLORIDE-INDUCED DURABILITY ANALYSIS

Bayesian model updating refers to a technique based on prior knowledge and up to date observations, which has the computational capability to reduce the uncertainties in engineering models. By reinterpreting Bayesian updating problem into a structural reliability problem, the state-of-the-art BUS algorithm (i.e., Bayesian updating with structural reliability methods) opens a new avenue for a fast and robust posterior density estimation. Towards the goal of fast and accurate parameter updating for a chloride-induced durability model, this paper adopts the subset simulation-based BUS approach. The computational efficiency and accuracy of the approach are demonstrated through investigating an engineering-guided sophisticated concrete durability model. Results showcase that the statistical properties of model parameters can be successfully updated by the information monitored in-situ and are close to the results estimated through simple rejection sampling.