structural behaviour of concrete structures.pdf

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  • 1 Structures Department, LNEC, Lisbon, Portugal

    Controlling the Structural Behaviour of Concrete Structures Using Model Updating and Low-Cost Monitoring

    Tiago Coelho R&D Grand Holder, MEng1

    Joo P. Santos PHD Student1

    Paulo Silveira Full Research Officer1

    The present work addresses the Structural Health Monitoring of large concrete structures, more specifically of large pre-stressed concrete bridges with high social and economic importance. Long concrete structures are prone to damage and malfunctions due to the effects of concrete rheological effects, namely creep and shrinkage. This fact has motivated multiple research and practical SHM works to address their study and experimental validation using embedded strain gages, whether deployed within the concrete medium or fixed to the steel reinforcement bars. This strategy has been long used and proved effective for studying and controlling the overall extensions observed throughout structural systems. However, a proper characterization of these effects requires that multiple cross-sections be instrumented with a large number of these sensors. This requirement renders this type of civil structural monitoring systems expensive, not only due to the large amount of sensors, but also due to the need of deploying acquisition units with a high number of input and signal conditioning boards.

    Displacement SensorStrain Gages + Thermometers

    0 100 200 300 400 500 600

    -10

    0-50

    050

    100

    Time Index (Days)

    Stra

    in (um

    /m)

    C10mC2mC4m

    0 100 200 300 400 500 600

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    0-50

    050

    100

    Time Index (Days)

    Dis

    place

    ments

    (m

    m) NL2

    NL3NL4

    (a)

    (b) (c)

    Fig 1 (a) Salgueiro Maia Bridge side view; (b) Average strain measurements; (c) Displacement measurements.

    The present work aims at proposing an alternative and inexpensive solution for controlling these effects on concrete structures. It relies on few inexpensive measurements of global structural displacements (in opposition to localized strain measurement) and in model updating. While strain measurement allows for a direct

  • 1 Structures Department, LNEC, Lisbon, Portugal

    characterization of strain across an entire structural system; the displacements do not, and are included in an automated model updating to infer the most compatible strain loadings being measured on a target structure. The case study addressed herein is the 250m span cable-stayed Salgueiro Maia Bridge, located in Santarm, Portugal (Fig.1a), which crosses the Tagus river 70km upstream of Lisbon. The structural system comprises a box-girder deck 2.62m high and 27.7m wide, suspended across a length of 489m by seventy two stay cables sheathed in steel tubes. The work described in this paper resorts to strain and temperature measurements obtained from three cross-sections, one from each pylon and one from the mid central span (Fig.1a); and to three hydrostatic pressure cells (located in the quarter and mid central span, Fig.1a) which measure the vertical displacements in comparison to a reference cell located over one pier. These measurements were conducted during a period of approximately two years and are shown in Fig.1a,b.

    0.5 1.0 1.5 2.0 2.5 3.0

    0.5

    1.0

    1.5

    2.0

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    f(Hz) Numerical

    f(Hz) E

    xpe

    rime

    nta

    l

    R=0.9986

    Fig 2 Numerical model of the Salgueiro Maia Bridge: correlation between numerical and experimentally obtained modal frequencies.

    The model updating task was conducted using a tri-dimensional numerical model (Fig.2) of the Salgueiro Maia Bridge which was previously updated using the latest results from a modal experimental campaign conducted on that structure. Using this model, combinations of strain loading magnitudes were applied to the deck and pylons within the range of 0 to 60 um/m, thus leading to a total amount of 216000 different load cases. The entire analysis was conducted using time-history analyses for computational simplicity. It was observed that all load cases could be run in only a few minutes, thus discarding the need for optimization techniques. From the 216000 analyses, the values of displacements obtained on the quarter and mid central span of the numerical model were obtained and compared to those obtained on site (Fig.1c). Several correlation / distance measures were used and the experimental displacement data was supressed of temperature effects using regression analysis with displacements as output and the measured temperatures as input. The load cases which generated displacements sets exhibit larger correlations / smaller distances to those measured on site were chosen as the ones which more accurately described the structural evolution generated by rheological effects during the monitoring period. The comparison of these load cases with the strain measurements conducted on site (Fig.2c), which were also suppressed of temperature effects using regression analysis, allowed concluding about the effectiveness of the proposed strategy.