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Seismic assessment of a railway masonry arch bridge using sensor-based model updating

Seismic assessment of a railway masonry arch bridge using sensor-based model updating
Seismic assessment of a railway masonry arch bridge using sensor-based model updating

A large part of Iranian railway bridge asset comprises masonry arch bridges, which have been in service for over 70 years. Seismic assessment of such structures is of great importance, particularly for high-seismic regions. Hence, this study assesses the seismic performance of Veresk masonry arch bridge, the longest masonry arch bridge of Iranian railway network (a span length of 99 m), spanned over a valley of depth 110 m, through a reliable sensor-based model updating. Dynamic tests are carried out using a test train, composed of 6-axle locomotives and 4-axle freight wagons, which travels across the bridge, and subsequently, vibration response of the instrumented bridge is measured. A high-fidelity 3D Finite Element (FE) model of the bridge is developed and updated using the measured vibration characteristics: mid-span displacements and natural frequencies. Finally, the seismic performance assessment of the bridge is performed through non-linear static and dynamic analyses for two seismic hazard levels with return periods of 150 and 1000 years. It is found that for the hazard level with a return period of 150 years, both nonlinear static and dynamic analyses give very similar results. However, for the seismic hazard level with the return period of 1000 years, the results of the static analysis are more conservative.

Field Tests, Finite Element Model, Masonry Bridge, Model Updating, Seismic Performance Assessment, UN SDG 9: Industry innovation and infrastructure
1478-4637
Tajali, Mosabreza
03c8747d-cfef-41e2-9ea9-2f35e907d84e
Ataei, Shervan
5d01e505-b9a2-4c93-bed0-6963cda2c91d
Miri, Amin
de8eef13-079d-41b4-b5ae-cf59db214c86
Ahmadi, Ehsan
f1994ae0-2b3e-43c9-a595-032e801aae70
Kashani, Mohammad M.
d1074b3a-5853-4eb5-a4ef-7d741b1c025d
Tajali, Mosabreza
03c8747d-cfef-41e2-9ea9-2f35e907d84e
Ataei, Shervan
5d01e505-b9a2-4c93-bed0-6963cda2c91d
Miri, Amin
de8eef13-079d-41b4-b5ae-cf59db214c86
Ahmadi, Ehsan
f1994ae0-2b3e-43c9-a595-032e801aae70
Kashani, Mohammad M.
d1074b3a-5853-4eb5-a4ef-7d741b1c025d

Tajali, Mosabreza, Ataei, Shervan, Miri, Amin, Ahmadi, Ehsan and Kashani, Mohammad M. (2022) Seismic assessment of a railway masonry arch bridge using sensor-based model updating. Proceedings of the Institution of Civil Engineers: Bridge Engineering. (doi:10.1680/jbren.22.00019).

Record type: Article

Abstract

A large part of Iranian railway bridge asset comprises masonry arch bridges, which have been in service for over 70 years. Seismic assessment of such structures is of great importance, particularly for high-seismic regions. Hence, this study assesses the seismic performance of Veresk masonry arch bridge, the longest masonry arch bridge of Iranian railway network (a span length of 99 m), spanned over a valley of depth 110 m, through a reliable sensor-based model updating. Dynamic tests are carried out using a test train, composed of 6-axle locomotives and 4-axle freight wagons, which travels across the bridge, and subsequently, vibration response of the instrumented bridge is measured. A high-fidelity 3D Finite Element (FE) model of the bridge is developed and updated using the measured vibration characteristics: mid-span displacements and natural frequencies. Finally, the seismic performance assessment of the bridge is performed through non-linear static and dynamic analyses for two seismic hazard levels with return periods of 150 and 1000 years. It is found that for the hazard level with a return period of 150 years, both nonlinear static and dynamic analyses give very similar results. However, for the seismic hazard level with the return period of 1000 years, the results of the static analysis are more conservative.

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e-pub ahead of print date: 23 August 2022
Additional Information: Publisher Copyright: © 2022 ICE Publishing: All rights reserved.
Keywords: Field Tests, Finite Element Model, Masonry Bridge, Model Updating, Seismic Performance Assessment, UN SDG 9: Industry innovation and infrastructure

Identifiers

Local EPrints ID: 470606
URI: http://eprints.soton.ac.uk/id/eprint/470606
ISSN: 1478-4637
PURE UUID: 896be109-9333-4756-981b-d93d889a8b23
ORCID for Mohammad M. Kashani: ORCID iD orcid.org/0000-0003-0008-0007

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Date deposited: 14 Oct 2022 16:36
Last modified: 17 Mar 2024 07:31

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Contributors

Author: Mosabreza Tajali
Author: Shervan Ataei
Author: Amin Miri
Author: Ehsan Ahmadi

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