Mosabreza Tajali, Shervan Ataei, A. Miri, E. Ahmadi, M. Kashani
{"title":"基于传感器模型更新的铁路砌体拱桥抗震评估","authors":"Mosabreza Tajali, Shervan Ataei, A. Miri, E. Ahmadi, M. Kashani","doi":"10.1680/jbren.22.00019","DOIUrl":null,"url":null,"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.","PeriodicalId":44437,"journal":{"name":"Proceedings of the Institution of Civil Engineers-Bridge Engineering","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2022-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Seismic Assessment of a Railway Masonry Arch Bridge Using Sensor-Based Model Updating\",\"authors\":\"Mosabreza Tajali, Shervan Ataei, A. Miri, E. Ahmadi, M. Kashani\",\"doi\":\"10.1680/jbren.22.00019\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":44437,\"journal\":{\"name\":\"Proceedings of the Institution of Civil Engineers-Bridge Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2022-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Institution of Civil Engineers-Bridge Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1680/jbren.22.00019\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Civil Engineers-Bridge Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1680/jbren.22.00019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
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.