Experimental Vibration Analysis for Civil Engineering Structures: EVACES 2023 - Volume 2

Author:   Maria Pina Limongelli ,  Pier Francesco Giordano ,  Said Quqa ,  Carmelo Gentile
Publisher:   Springer International Publishing AG
Edition:   2023 ed.
Volume:   433
ISBN:  

9783031391163


Pages:   763
Publication Date:   29 August 2023
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Experimental Vibration Analysis for Civil Engineering Structures: EVACES 2023 - Volume 2


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Overview

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.

Full Product Details

Author:   Maria Pina Limongelli ,  Pier Francesco Giordano ,  Said Quqa ,  Carmelo Gentile
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   2023 ed.
Volume:   433
Weight:   1.334kg
ISBN:  

9783031391163


ISBN 10:   3031391160
Pages:   763
Publication Date:   29 August 2023
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

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.

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