Tanaro Bridge: Dynamic Tests on a Couple of Spans

Brencich, Antonio; Sabia, Donato

doi:10.1061/(asce)1084-0702(2007)12:5(662)

Cited by 10 publications

(6 citation statements)

References 10 publications

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“…For these reasons, finite elements (FE) and macro-elements are often preferred for the seismic assessment of real case studies in the current practice. 2D and 3D FE models (Pelà et al, 2013) allow for representing the effect of fill soil, spandrel walls and backings on the dynamic behaviour of the bridge, as revealed by field testing and dynamic monitoring (Brencich and Sabia, 2007;Mautner and Reiterer, 2007). Nevertheless, the high computational effort required by 3D FE models for time-step simulations makes them unfeasible for applications to large multi-span bridges, especially in current design practice.…”

Section: Seismic Assessment Approachesmentioning

confidence: 99%

A review of experimental investigations and assessment methods for masonry arch bridges

Sarhosis

Santis

Felice

2016

Structure and Infrastructure Engineering

117

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Masonry arch bridges constitute a significant proportion of European road and rail infrastructures.Most of them are well over 100 years old and are supporting traffic loads many times above those originally envisaged. The inherent variation in their constituent materials, the traditional design criteria and methods used for their construction, their deterioration over time caused by weathering processes and the development of other defects, significantly influence the mechanical response of these historic structures. A deep understanding on the numerous factors that affect the structural behaviour of masonry arch bridges and on the analysis methods to assess the life expectancy of such bridges and inform maintenance and strengthening strategies is essential. This paper provides a critical review of the experimental studies that have been carried out and of the assessment approaches that have been developed in the last three decades to these aims. The current knowledge is established and areas of possible future research work are identified, with the aim of providing students and researchers, asset managers and bridge owners, and practitioners with a guidance for research activities and maintenace strategies.

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Section: Seismic Assessment Approachesmentioning

confidence: 99%

A review of experimental investigations and assessment methods for masonry arch bridges

Sarhosis

Santis

Felice

2016

Structure and Infrastructure Engineering

117

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“…Static and dynamic load test is a part of acceptance procedure for new bridges in Latvia and in many other countries around the world (Burdet, Corthay 1995;Karoumi, Andersson 2007;Cunha et al 2008;Brencic, Sabia 2007;Akimovs, Paeglītis 2008;Paeglite, Paeglitis 2013). The bridge load testing in Latvia is performed according to the requirements of the national standard LVS 190-11: 2009.…”

Section: Dynamic Load Testingmentioning

confidence: 99%

Dynamic Amplification Factor for Bridges With Span Length From 10 to 35 Meters

Paeglīte

Paeglītis

Smirnovs

2015

Engineering Structures and Technologies

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Heavy traffic on the bridge cause not only static effects, but also dynamic effects. These effects can be indicated by different dynamic parameters like -natural frequency, bridge logarithmical decrement, bridge acceleration and dynamic amplification factor (DAF). Dynamic amplification factor is the most widely used parameter, because it shows amplification of the static effects on the bridge structure. Results show that for bridges road surface condition is a very important factor. If road surface contains ice bumps or potholes then heavy traffic driving with low speed can decrease load carrying capacity of a bridge.

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“…However, the model formulation must be appropriate enough to characterize the actual structure. [5][6][7][8][9][10] In the data-driven approach, no assumptions are made about the mechanism underlying the experimental data. The model selected for describing the relevant characteristics of the system is built on top of the data and has not any specific physical meaning (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…However, the model formulation must be appropriate enough to characterize the actual structure. 5–10…”

Section: Introductionmentioning

confidence: 99%

A machine learning approach for the automatic long-term structural health monitoring

Demarie

Sabia

2018

Structural Health Monitoring

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Measuring the response of a structure to the ambient and service loads is a source of information that can be used to estimate some important engineering parameters or, to a certain extent, to characterize the structural behavior as a whole. By repeating the data acquisition over a period of time, it is possible to check for variations in the structure’s response, which may be correlated to the appearance or growth of a damage (e.g. following some exceptional event as the earthquake, or as a consequence of materials and components aging). The complexity of some existing structures and their environment very often requires the execution of a monitoring plan in order to support analyses and decisions through the evidence of measured data. If the monitoring is implemented through a sensor network continuously acquiring over time, then the evolution of the structural behavior may be tracked continuously as well. Such approach has become a viable option for practical applications since the last decade, as a consequence of the progress in the data acquisition and storage systems. However, proper methods and algorithms are needed for managing the large amount of data and the extraction of valuable knowledge from it. This article presents a methodology aimed at making automatic the process of structural monitoring in case it is carried continuously over time. It relies on some existing methods from the machine learning and data mining fields, which are casted into a process targeted to delimit the need of the human being intervention to the training phase and the engineering judgment of the results. The methodology has been successfully applied to the real-world case of an ancient masonry bell tower, the Ghirlandina Tower (Modena, Italy), where a network made of 12 accelerometers and 3 thermocouples has been acquiring continuously since August 2012. The structural characterization is performed by identifying the first modes of vibration, whose evolution over time has been tracked.

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Tanaro Bridge: Dynamic Tests on a Couple of Spans

Cited by 10 publications

References 10 publications

A review of experimental investigations and assessment methods for masonry arch bridges

A review of experimental investigations and assessment methods for masonry arch bridges

Dynamic Amplification Factor for Bridges With Span Length From 10 to 35 Meters

A machine learning approach for the automatic long-term structural health monitoring

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