1. Αποθετήριο Παραδοτέων Υποτρόφων Δράσεων ΕΣΠΑ Τριτοβάθμιας Εκπαίδευσης 2017-2023
2. Όλο το Αποθετήριο
3. Ερευνητικές ομάδες

Τύπος:	Πρακτικά συνεδρίου
Τίτλος:	Machine learning techniques for the estimation of limit state thresholds and bridge-specific fragility analysis of R/C bridges
Συγγραφέας:	[EL] Στεφανίδου, Σωτηρία[EN] Stefanidou, Sotiria [EL] Παπανικολάου, Βασίλειος[EN] Papanikolaou, Vasileios [EL] Παρασκευόπουλος, Ηλίας[EN] Paraskevopoulos, Elias [EL] Κάππος, Ανδρέας[EN] Kappos, Andreas
Ημερομηνία:	Ιου-2021
Περίληψη:	Based on past earthquake events, bridges are the most critical and usually the most vulnerable components of road and rail transport systems, while bridge damage is related to substantial direct and indirect losses. In view of this, the need for direct and reliable assessment of bridge vulnerability has emerged, and several methodologies have been developed using probabilistic analysis for the derivation of fragility curves. A new framework for the derivation of bridge-specific fragility curves is proposed herein, introducing machine learning techniques for a reliable estimation of limit state thresholds of the most critical component of the bridge system (which in standard -ductility based- design is the piers), in terms of a widely used engineering demand parameter, i.e. displacement of control point. A set of parameters affecting the seismic capacity and the failure modes of bridge piers is selected, including geometry, material properties, and reinforcement ratios for cylindrical piers. Training and test sets are generated from multiple inelastic pushover analyses of the pier component, and Artificial Neural Networks (ANN) analysis is performed to derive closed-form relationships for the estimation of limit state thresholds. The latter are compared with closed-form relationships available in the literature, highlighting the effect of machine learning techniques on the reliable estimation of bridge fragility curves for all damage states.
Γλώσσα:	Αγγλικά
Τόπος δημοσίευσης:	Αθήνα, Ελλάδα
Σελίδες:	9
ISBN:	978-618-85072-5-8
ISSN:	2623-3347
Θεματική κατηγορία:	[EL] Δομοστατική[EN] Structural Engineering
Λέξεις-κλειδιά:	Bridge fragility curves; Limit state thresholds; Machine learning techniques; ANN
Κάτοχος πνευματικών δικαιωμάτων:	© Institute of Research & Development for Computational Methods in Engineering Sciences . All Rights Reserved
Ηλεκτρονική διεύθυνση του τεκμηρίου στον εκδότη:	https://2021.compdyn.org/proceedings/pdf/19544.pdf
Ηλεκτρονική διεύθυνση περιοδικού:	https://2021.compdyn.org/proceedings/
Τίτλος πηγής δημοσίευσης:	Proceedings of the International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering. 8th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering
Όνομα εκδήλωσης:	8th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering
Τοποθεσία εκδήλωσης:	Streamed from Athens, Greece
Ημ/νία έναρξης εκδήλωσης:	28/06/2021
Ημ/νία λήξης εκδήλωσης:	30/06/2021
Σημειώσεις:	“This research was co-financed by Greece and the European Union (European Social FundESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning 2014- 2020» in the context of the project “Online database for the development of fragility curves for as-built and retrofitted RC bridges using machine learning techniques” (MIS 5047878).
Εμφανίζεται στις συλλογές:	Ερευνητικές ομάδες