2023 Volume 79 Issue 15 Article ID: 22-15005
The performance of existing structures varies over time due to aging and damage caused by various environmental factors. Therefore, it is necessary to properly assess the residual performance for their lifecycle management. For this purpose, it is essential to calibrate the numerical model based on observations, so that the model responses are tuned as close as possible to the actual behaviors. In this study, we propose a hierarchical Bayesian model updating framework using the Bhattacharyya distance and staircase density functions to quantify uncertainties in the model parameters. Through simple numerical examples, the proposed method is compared with the conventional Bayesian inference. The results demonstrate that the proposed method is robust to various distribution shapes and capable of quantifying various types of uncertainties such as measurement errors or/and model parameter uncertainties.
