Enhancing structural performance prediction through Bayesian updating with considering load and speed uncertainty

Finite-Element (FE) models, crucial for predicting structural responses, often rely on oversimplified assumptions, contrasting sharply with real-world data obtained through Structural Health Monitoring (SHM). To enhance the accuracy of these predictions, Bayesian updating techniques are employed, underscoring the significance of integrating comprehensive knowledge, including uncertainties in load and speed. These techniques refine structural models by merging prior engineering insights with SHM data. This paper delves into the latest advancements in Bayesian updating and their practical application for engineers. A case study featuring a simple beam model under a moving load showcases these methods’ applicability, highlighting the importance of updating structural parameters by incorporating all available prior knowledge, especially regarding load and speed conditions. Our findings bolster ongoing efforts to ensure the reliability and safety of bridge structures amid evolving transportation demands.