University of Illinois at Chicago
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Mechanism Methodology for Structural Health Monitoring of Arch Bridges

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posted on 2012-12-09, 00:00 authored by Chad R. Fischer
There are numerous in-service masonry arch bridges across Europe, India, and North America. As these bridges age and deteriorate, it is important to be able to safely evaluate them for the allowable loads that they can support. Structural health monitoring systems using fiber optic sensors are valuable tools that can provide real-time feedback about the movement and performance of the arch structures under railway and traffic loads. Sensors can measure parameters such as crack opening displacements, bridge deflections, support movements, thermal fluctuations, and vibrations. However, monitoring systems are only successful if there is proven baseline against which to compare the measured data. Many theories and methodologies have been previously developed to calculate the ultimate strength, or load carrying capacity of masonry arch bridges. However, none of these analysis methods were able to provide estimates of real-time bridge performance under service loading conditions. In order to address these concerns, a new methodology for analyzing masonry arches is proposed using a combination of rigid block analysis and finite element modeling. There is a need for simplified methods for rapid analysis of masonry arches using generic finite element programs. Such methods provide the opportunity for interpretation of data from structural health monitoring systems. To fill this gap, a methodology has been proposed in this dissertation for accurate, yet simple analysis of masonry arches. The proposed methodology was validated with a series of scaled masonry arch tests in the laboratory. It was then implemented to understand data from a structural health monitoring system installed on the masonry approach arches of the Brooklyn Bridge.

History

Advisor

Ansari, Farhad

Department

Civil and Materials Engineering

Degree Grantor

University of Illinois at Chicago

Degree Level

  • Doctoral

Committee Member

McNallan, Michael Karpov, Eduard Ozevin, Didem Mufti, Aftab

Submitted date

2011-12

Language

  • en

Issue date

2012-12-09

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