Ghini, Emma
(2022)
Loading and damage modelling for an integrated SHM system of a prestressed concrete railway bridge in Naples.
[Laurea magistrale], Università di Bologna, Corso di Studio in
Civil engineering [LM-DM270], Documento full-text non disponibile
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Abstract
The thesis explores recent technology developments in the field of structural health monitoring and its application to railway bridge projects. It focuses on two main topics. First, service loads and effect of environmental actions are modelled. In particular, the train moving load and its interaction with rail track is considered with different degrees of detail. Hence, results are compared with real-time experimental measurements. Secondly, the work concerns the identification, definition and modelling process of damages for a prestressed concrete railway bridge, and their implementation inside FEM models. Along with a critical interpretation of the in-field measurements, this approach results in the development of undamaged and damaged databases for the AI-aided detection of anomalies and the definition of threshold levels to prompt automatic alert interventions. In conclusion, an innovative solution for the development of the railway weight-in-motion system is proposed.
Abstract
The thesis explores recent technology developments in the field of structural health monitoring and its application to railway bridge projects. It focuses on two main topics. First, service loads and effect of environmental actions are modelled. In particular, the train moving load and its interaction with rail track is considered with different degrees of detail. Hence, results are compared with real-time experimental measurements. Secondly, the work concerns the identification, definition and modelling process of damages for a prestressed concrete railway bridge, and their implementation inside FEM models. Along with a critical interpretation of the in-field measurements, this approach results in the development of undamaged and damaged databases for the AI-aided detection of anomalies and the definition of threshold levels to prompt automatic alert interventions. In conclusion, an innovative solution for the development of the railway weight-in-motion system is proposed.
Tipologia del documento
Tesi di laurea
(Laurea magistrale)
Autore della tesi
Ghini, Emma
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Indirizzo
Structural Engineering
Ordinamento Cds
DM270
Parole chiave
Post-Tensioned Prestressed Concrete Bridge,Structural Health Monitoring,Damage,Train Load,Weight-In-Motion,AI-aided Anomaly Detection
Data di discussione della Tesi
20 Luglio 2022
URI
Altri metadati
Tipologia del documento
Tesi di laurea
(NON SPECIFICATO)
Autore della tesi
Ghini, Emma
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Indirizzo
Structural Engineering
Ordinamento Cds
DM270
Parole chiave
Post-Tensioned Prestressed Concrete Bridge,Structural Health Monitoring,Damage,Train Load,Weight-In-Motion,AI-aided Anomaly Detection
Data di discussione della Tesi
20 Luglio 2022
URI
Gestione del documento: