Model Updating Using Bridge Influence Lines Based on an Adaptive Metamodel Global Optimization Method

Abstract

Model updating seeks to update a finite-element model to reduce discrepancies between predicted and measured data. Metamodel-based model updating using bridge influence lines is a very promising method. However, the accuracy of traditional metamodel methods is not high due to the traditional metamodels being fitted in the entire parameter space using limited sample data. To address this problem, a model updating procedure based on the adaptive metamodel global optimization method is proposed. First, a systematic model updating theory using influence lines is developed, including three different objective functions and a selection of model updating parameters. Then, the adaptive metamodel-based global optimization method is proposed. The adaptive metamodel is iteratively fitted using the automatically added sample data by the mode-pursuing sampling method in the process of optimization. To improve the efficiency of finding the global optimal solution, a two-stage optimization strategy is presented. Finally, the proposed procedure is applied to numerical and practical examples of a long-span suspension bridge. In the numerical example, the global optimal solution is found successfully compared with the traditional metamodels. Excellent agreements are observed between the updated influence lines and measured influence lines in both numerical and practical examples. Based on the proposed theory, the accuracy and efficiency of model updating can well meet engineering requirements.