Exploring physics-enhanced neural operators for predicting vehicle-bridge dynamics: From 1-DOF to 13- DOF vehicle models

Key Points

• Vehicle-bridge dynamics prediction shows significant accuracy improvements over traditional models, indicating high relevance for engineering applications.
• The analysis involved transitioning from 1-DOF to 13-DOF models, demonstrating the flexibility and precision of the neural operators employed in the study.
• Using physics-enhanced neural operators allowed for more dynamic response considerations, integrating complex interactions between vehicles and structures.
• This method supports future investigations into more intricate models, highlighting potential for better structural integrity assessments.