
Experimental Vibration Analysis for Civil Engineering Structures
EVACES 2023 - Volume 2
Springer (Publisher)
Published on 29. August 2023
Book
Hardback
XX, 763 pages
978-3-031-39116-3 (ISBN)
Description
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 human-structure, vehicle-structure, and soil-structureinteraction); and application of advanced techniques involving the Internet of Things, robot, UAV, big data and artificial intelligence.
More details
Series
Edition
2023 ed.
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
76 s/w Abbildungen, 430 farbige Abbildungen
XX, 763 p. 506 illus., 430 illus. in color.
Dimensions
Height: 241 mm
Width: 160 mm
Thickness: 48 mm
Weight
1326 gr
ISBN-13
978-3-031-39116-3 (9783031391163)
DOI
10.1007/978-3-031-39117-0
Schweitzer Classification
Other editions
Additional editions

Maria Pina Limongelli | Pier Francesco Giordano | Said Quqa
Experimental Vibration Analysis for Civil Engineering Structures
EVACES 2023 - Volume 2
Book
08/2024
Springer
€299.59
Shipment within 15-20 days

Maria Pina Limongelli | Pier Francesco Giordano | Said Quqa
Experimental Vibration Analysis for Civil Engineering Structures
EVACES 2023 - Volume 2
E-Book
08/2023
1st Edition
Springer
€287.83
Available for download
Content
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.