Bayesian estimate of the elastic modulus of concrete box girders from dynamic identification: a statistical framework for the A24 motorway in Italy

Aloisio, Angelo; Pasca, Dag Pasquale; Alaggio, Rocco; Fragiacomo, Massimo

doi:10.1080/15732479.2020.1819343

Cited by 24 publications

(8 citation statements)

References 23 publications

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“…The author solved the optimization problem described in Equation ( 15) by using the input parameters in Table 1 and the experimental values in Table 2; the first natural frequency and the elastic modulus from the static load test. The use of the first natural frequency depends on the good accordance between the first mode shape and that of a simply supported beam, as remarked in [53]. This supports the use of Equation (6) in Equation (15).…”

Section: Resultssupporting

confidence: 62%

“…The Stochastic-Subspace Identification (SSI) method returned an estimate of the modal parameters [49][50][51]. The reader might find sufficient details about the girders, the experimental setup and the results of operational modal analysis in the following research papers [51][52][53]. The author will avoid replicating the same information reported in these papers by focusing on the prestressing estimate.…”

Section: Testing Of the Procedures On A Real Case Problemmentioning

confidence: 99%

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Aspects of Vibration-Based Methods for the Prestressing Estimate in Concrete Beams with Internal Bonded or Unbonded Tendons

Aloisio

2021

Infrastructures

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The estimate of internal prestressing in concrete beams is essential for the assessment of their structural reliability. Many scholars have tackled multiple and diverse methods to estimate the measurable effects of prestressing. Among them, many experimented with dynamics-based techniques; however, these clash with the theoretical independence of the natural frequencies of the forces of internally prestressed beams. This paper examines the feasibility of a hybrid approach based on dynamic identification and the knowledge of the elastic modulus. Specifically, the author considered the effect of the axial deformation on the beam length and the weight per unit of volume. It is questioned whether the uncertainties related to the estimate of the elastic modulus and the first natural frequency yield reasonable estimates of the internal prestressing. The experimental testing of a set of full-scale concrete girders with known design prestressing supports a discussion about its practicability. The author found that the uncertainty in estimating the natural frequencies and elastic modulus significantly undermines a reliable estimate of the prestressing state.

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Section: Resultssupporting

confidence: 62%

Section: Testing Of the Procedures On A Real Case Problemmentioning

confidence: 99%

Aspects of Vibration-Based Methods for the Prestressing Estimate in Concrete Beams with Internal Bonded or Unbonded Tendons

Aloisio

2021

Infrastructures

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“…ese paragraphs remark on the most significant outcomes of dynamic identification by discussing the role of bending stiffness in the beams' dynamics. Aloisio et al [1,42,43] focused on the dynamic identification of a set of seven PSC girders of the A24 motorway. e dynamic identification using two arrays of five accelerometers led to the identification of three stable modes.…”

Section: Remarks On the Experimental Dynamic Response Of The Tested Girders Using Fixed Sensorsmentioning

confidence: 99%

“…Despite the indispensability of human expertise, the status of a bridge cannot always stem from visual investigations. Objective, nondestructive tests with low time and money expense should be companions of the current prioritization methods based on visual inspections [1]. e primary outcomes of static load tests are momentdeflection curves, which estimate the bending stiffness and, consequently, the elastic modulus.…”

Section: Introductionmentioning

confidence: 99%

Experimental Estimation of the Elastic Modulus of Concrete Girders from Drive‐By Inspections with Force‐Balance Accelerometers

Aloisio

Alaggio

2021

Shock and Vibration

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Parametric identification of bridges using instrumented vehicles can be challenging, mainly due to the reduced length of the time series associated with the bridge span under test. This research discusses the practicability of a time-domain identification method based on the use of an instrumented vehicle. The highest cross-correlation between the bridge response from an elementary analytical model and the experimental one, acquired by a moving force-balance accelerometer, yields the unknown model parameter. The effect of vehicle-bridge interaction is removed by proper filtering of the signals. Specifically, the authors estimate the elastic moduli of seven prestressed concrete bridges and compare a subset of the results to the outcomes of static load tests carried out on the same bridges. There is a good correlation between the elastic moduli from the instrumented vehicle and those from static load tests: the method grasps the approximate value of the elastic modulus of concrete. Still, the data do not return an excellent match due to the bias in the estimation of the deflection shape—the paper remarks on the issues faced during the experimental tests and proposes possible enhancements of these procedures.

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“…Sustained long-term loads degrade the bridge’s function and can lead to major damage if the bridge becomes deformed [ 1 , 2 , 3 ]. In addition, aging bridges become quite vulnerable to natural disasters, such as earthquakes and floods, due to deterioration in performance [ 4 , 5 ]. Therefore, bridges are essential structures that require regular inspections.…”

Section: Introductionmentioning

confidence: 99%

LiDAR-Based Bridge Displacement Estimation Using 3D Spatial Optimization

Cha

Sim

Park

et al. 2020

Sensors

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As civil engineering structures become larger, non-contact inspection technology is required to measure the overall shape and size of structures and evaluate safety. Structures are easily exposed to the external environment and may not be able to perform their original functions depending on the continuous load for a long time. Therefore, in this study, we propose a method for estimating the vertical displacement of structures using light detection and ranging, which enables non-contact measurement. The point cloud acquired through laser scanning was rearranged into a three-dimensional space, and internal nodes were created by continuously dividing the space. The generated node has its own location information, and the vertical displacement value was calculated by searching for the node where the deformation occurred. The performance of the proposed displacement estimation technique was verified through static loading experiments, and the octree space partitioning method is expected to be applied and utilized in structural health monitoring.

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Bayesian estimate of the elastic modulus of concrete box girders from dynamic identification: a statistical framework for the A24 motorway in Italy

Cited by 24 publications

References 23 publications

Aspects of Vibration-Based Methods for the Prestressing Estimate in Concrete Beams with Internal Bonded or Unbonded Tendons

Aspects of Vibration-Based Methods for the Prestressing Estimate in Concrete Beams with Internal Bonded or Unbonded Tendons

Experimental Estimation of the Elastic Modulus of Concrete Girders from Drive‐By Inspections with Force‐Balance Accelerometers

LiDAR-Based Bridge Displacement Estimation Using 3D Spatial Optimization

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