This volume presents peer-reviewed contributions from the 10th International Conference on Experimental Vibration Analysis for Civil Engineering Structures (EVACES), held in Milan, Italy on August 30-September 1, 2023. The event brought together engineers, scientists, researchers, and practitioners, providing a forum for discussing and disseminating the latest developments and achievements in all major aspects of dynamic testing for civil engineering structures, including instrumentation, sources of excitation, data analysis, system identification, monitoring and condition assessment, in-situ and laboratory experiments, codes and standards, and vibration mitigation. The topics included but were not limited to: damage identification and structural health monitoring; testing, sensing and modeling; vibration isolation and control; system and model identification; coupled dynamical systems (including humanstructure, vehiclestructure, and soilstructureinteraction); and application of advanced techniques involving the Internet of Things, robot, UAV, big data and artificial intelligence.

Presents the latest developments in experimental vibration analysis for civil engineering Covers a wide range of topics such as damage identification, vibration control, and coupled dynamical systems Features applications of advanced techniques involving artificial intelligence and the Internet of Things

Inhalt
Optimization of structural health monitoring for bridges networks by combining traditional and innovative techniques.- Value of Seismic Structural Health Monitoring Information for management of civil structures under different prior knowledge scenarios.- On the modeling of multi-sensors vibration-based monitoring systems and integrity management.- Efficient subspace-based operational modal analysis using video-based vibrationmeasurements.- Model order selection for uncertainty quantification in subspace-based OMA of Vestas V27 blade.- Modal Analysis of a Steel Truss Bridge under Varying Environmental Conditions.- Linear System Identification and Bayesian Model Updating of the UC San Diego Geisel Library.- FE model updating of cable-stayed bridges based on the experimental estimate of cable forces and modal parameters.- Physics-based and machine-learning models for braking impact factors.- Dynamic tests with hard braking heavy vehicles on a motorway bridge.- Determining braking forces on bridges using monitored traffic data and stochastic simulation.- Fusing modal parameters and curvature influence lines for damage localization under vehicle excitation.- An Unsupervised Learning Method for Indirect Bridge Structural Health Monitoring.- Using contact residual responses of a 3-DOF scooter to identify first few frequencies of the footbridge.- Automatic drive-by bridge damage detection via a clustering algorithm.- A Drive-by Bridge Damage Localisation Method with an Instrumented Vehicle.- A Data-Driven Approach for Monitoring Railway Tracks using Dynamic Responses Collected by an In-Service Train.- Bridge response fusion drive-by-bridge inspection by means of model updates.- Drive-by Bridge Deflection Estimating Method Based on Track Irregularities Measured on a Train: Extension to Multiple Bridge Sections.- Roadway roughness profile identification from vehicle acceleration by means of dynamic regularized least square minimization.