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Abstract
This study investigates fatigue behavior at the grain-scale in structural steel, a crucial issue for ensuring the safety and dependability of steel bridges in modern railway transportation systems. The field of bridge engineering has undergone significant transformation in recent years, transitioning from wrought iron to contemporary structural steels, resulting in a revolutionary impact on methodologies.
The study uses a two-fold methodology, integrating computational models and experimental validation, to understand fatigue at the grain level. Using numerical crystal plasticity finite element (CPFE) modeling, it provides a comprehensive understanding of microstructural characteristics' impact on fatigue performance. This evaluation is crucial for assessing fatigue susceptibility in existing bridges, especially those built using older technologies and exposed to modern traffic demands.
This study analyzes the relationship between microscale and mesoscale fatigue behavior using CPFE RVE analysis and FeSafe simulations. It examines the impact of microstructural characteristics on fatigue start and propagation, while providing forecasts of macroscopic fatigue behaviors under realistic loading situations. Comparing stress-life curves at grain-scale and mesoscale levels provides insight into the material's overall fatigue behavior.
In essence, this study provides a comprehensive understanding of the fatigue characteristics at the grain level in structural steel, so acting as a fundamental contribution to the progress of materials science and engineering methodologies. The study provides a comprehensive analysis of fatigue mechanisms by integrating microscale insights with macroscopic fatigue responses. This not only enhances our understanding of fatigue mechanisms but also provides practical guidance for the design and maintenance of durable bridges that can withstand the challenging conditions of contemporary railway transportation systems.
Abstract
This study investigates fatigue behavior at the grain-scale in structural steel, a crucial issue for ensuring the safety and dependability of steel bridges in modern railway transportation systems. The field of bridge engineering has undergone significant transformation in recent years, transitioning from wrought iron to contemporary structural steels, resulting in a revolutionary impact on methodologies.
The study uses a two-fold methodology, integrating computational models and experimental validation, to understand fatigue at the grain level. Using numerical crystal plasticity finite element (CPFE) modeling, it provides a comprehensive understanding of microstructural characteristics' impact on fatigue performance. This evaluation is crucial for assessing fatigue susceptibility in existing bridges, especially those built using older technologies and exposed to modern traffic demands.
This study analyzes the relationship between microscale and mesoscale fatigue behavior using CPFE RVE analysis and FeSafe simulations. It examines the impact of microstructural characteristics on fatigue start and propagation, while providing forecasts of macroscopic fatigue behaviors under realistic loading situations. Comparing stress-life curves at grain-scale and mesoscale levels provides insight into the material's overall fatigue behavior.
In essence, this study provides a comprehensive understanding of the fatigue characteristics at the grain level in structural steel, so acting as a fundamental contribution to the progress of materials science and engineering methodologies. The study provides a comprehensive analysis of fatigue mechanisms by integrating microscale insights with macroscopic fatigue responses. This not only enhances our understanding of fatigue mechanisms but also provides practical guidance for the design and maintenance of durable bridges that can withstand the challenging conditions of contemporary railway transportation systems.
Tipologia del documento
Tesi di laurea
(Laurea magistrale)
Autore della tesi
Noureldin Mubarak Mohamed Ahmed, Mohamed
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Indirizzo
Historic buildings rehabilitation
Ordinamento Cds
DM270
Parole chiave
Grainscale Fatigue Modelling, Bridges Materials, Multiscale Fatigue Analysis, CPFEM
Data di discussione della Tesi
14 Settembre 2023
URI
Altri metadati
Tipologia del documento
Tesi di laurea
(NON SPECIFICATO)
Autore della tesi
Noureldin Mubarak Mohamed Ahmed, Mohamed
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Indirizzo
Historic buildings rehabilitation
Ordinamento Cds
DM270
Parole chiave
Grainscale Fatigue Modelling, Bridges Materials, Multiscale Fatigue Analysis, CPFEM
Data di discussione della Tesi
14 Settembre 2023
URI
Gestione del documento: