Model for forecasting the time of corrosion-induced reinforced concrete cracking

Lv, Qingfang; Ran, Zhu

doi:10.14264/uql.2016.511

Cited by 6 publications

(6 citation statements)

References 28 publications

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“…, 39 where both E c and f c are given in MPa. The reduced concrete strength due to cracking and spalling can be determined based on Equation (3), 28 which represents the reduction of compressive strength due to tensile strains in the transverse direction that cause longitudinal microcracks.…”

Section: Modeling Of Corrosionmentioning

confidence: 99%

Influence of modeling choices and prior information on the Bayesian assessment of a reinforced concrete bridge

Vereecken,

Botte,

Lombaert

et al. 2024

Structural Concrete

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A lot of bridges are aging and reaching the anticipated service life. To gain insight in their remaining resistance, inspections and measurements can be performed. The resulting information and data can be used to update variables in the degradation models of these bridges. To account for spatial variation, degradation variables can be modeled with random fields. The random fields of the degradation variables are updated based on a Bayesian inference procedure, where different types of heterogenous and indirect data are accounted for. Nevertheless, in this procedure, various assumptions need to be made, such as the quantification of measurement uncertainty, the structural and degradation model to be used, the prior distributions of the variables of interest, and so forth. These assumptions can influence the results of the Bayesian inference. Hence, in this work, it will be investigated what the influence is of different assumptions and how they affect the localization and quantification of damage. This will be done by application to a reinforced concrete girder bridge. The main conclusions are that the model used in the Bayesian inference procedure should resemble the actual structure as good as possible and that simplifications that are allowed in the design can lead to posterior distributions deviating a lot from the actual situation. Moreover, it is illustrated how information from visual observations can be included in the definition of the prior distributions and how this has a beneficial effect on the posterior predictions.

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Section: Modeling Of Corrosionmentioning

confidence: 99%

Influence of modeling choices and prior information on the Bayesian assessment of a reinforced concrete bridge

Vereecken,

Botte,

Lombaert

et al. 2024

Structural Concrete

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“…42 (

E_{c} = 22 {(\frac{f_{normalc}}{10})}^{0.3}

, with f c in MPa) and Ref. 43 (

E_{c} = 4500 \sqrt{f_{normalc}} false)

. Inserting the reduced concrete compressive strength according to Equation () leads to a reduced Young's modulus accounting for corrosion.…”

Section: Modeling Degradation Due To Prestress Corrosionmentioning

confidence: 99%

Assessment of corroded prestressed and posttensioned concrete structures: A review

Vereecken

Botte

Lombaert

et al. 2021

Structural Concrete

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Prestressed structures are commonly used all over the world. They might be subjected to degradation, such as corrosion of the prestressing steel. This can influence the resistance of these structures and induce early failure. Hence, prediction of the corrosion level is important in the assessment of existing prestressed structures. For this purpose, the corrosion process and the accompanying influences on the structure should be modeled. For reinforced concrete (RC) structures, a lot of research and guidelines are available to model the corrosion process. Nevertheless, this corrosion process might differ for prestressed structures, due to the different structural composition, the different geometry of the strands or tendons compared with reinforcement bars, the presence of the prestress, and so on. Moreover, for posttensioned structures, initiation and propagation of corrosion are even more different from corrosion in RC structures, due to the location of the steel in ducts and the lack of direct contact with the surrounding concrete. In this paper, a state‐of‐the‐art on the assessment of prestressed and posttensioned structures subjected to corrosion is given based on a literature review. Different models for the corrosion process and their influence on the structure are discussed. Comparison is made between reinforced, prestressed, and posttensioned structures. Furthermore, some assessment procedures are indicated and relevant topics for further research are given.

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“…In this work, an analytical model will be used for this reduced stiffness. In general, the Young's modulus of concrete can be written as a function of the compression strength (Lv & Zhu 2016):…”

Section: Degradation Modelmentioning

confidence: 99%

Detecting and localizing corrosion induced damage in reinforced concrete structures based on modal data

Vereecken¹,

Botte²,

Caspeele³

et al. 2021

Life-Cycle Civil Engineering: Innovation, Theory and Practice

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Reinforced concrete structures degrade over time, among others due to corrosion. This degradation process is not uniform along the structure. Monitoring and inspections can be used to detect damage and update a deterioration model of the structure. In this work, a model-based method is used to identify damage through the calibration of a FEM model based on modal characteristics. The model calibration is performed by means of a Bayesian method, using MCMC to sample the posterior distributions of model parameters for the time-dependent degradation of material properties. The calibrated model can then be used for a more accurate prediction of the remaining service life. Furthermore, it enables to be implemented in a pre-posterior analysis framework to determine the VoI of the monitoring and inspection program for comparison of different monitoring and inspection strategies.

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Model for forecasting the time of corrosion-induced reinforced concrete cracking

Cited by 6 publications

References 28 publications

Influence of modeling choices and prior information on the Bayesian assessment of a reinforced concrete bridge

Influence of modeling choices and prior information on the Bayesian assessment of a reinforced concrete bridge

Assessment of corroded prestressed and posttensioned concrete structures: A review

Detecting and localizing corrosion induced damage in reinforced concrete structures based on modal data

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