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Probabilistic Modelling of Containment Building Leakage at the Structural Scale: Application to the PACE Mock-Up
This work follows studies conducted in the framework of the French research program MaCEnA (PIA), aiming to predict air leakage through a reinforced (and prestressed) concrete structure. As mentioned by the international Benchmark VeRCoRs, only very few teams were able to predict them and variations of at least one order of magnitude between participants were observed.
Reinforced concrete tightness estimation is of the utmost importance for confinement vessels but also to assess concrete structures durability. One of the reasons for these difficulties lies in the fact that air leakage prediction is the last step of complex, multiphysics and coupled simulations. On the one hand, to predict concrete permeability, saturation evolution of the porous network needs to be correctly addressed. On the other hand, cracks predictions (numbers, openings, and appearance time) is essential but not sufficient since roughnesses, tortuosities and connectivities of these latter also strongly influence the leakage rate.
After a first part showing the capacity of the used model to mimic the behavior of a structural representative volume, this contribution quantifies the effect of the use of autocorrelated random fields modelling the tensile strength on the concrete structural leakage prediction. The results highlight that the air leakage prediction can easily vary by one order of magnitude for the same random field parameters. Moreover, during mechanical loading, observation of the cracks evolutions (numbers, openings and positions) allows for quantifying the prevalence of material and structural heterogeneity and explains the sudden evolution of leakage rate.
Probabilistic Modelling of Containment Building Leakage at the Structural Scale: Application to the PACE Mock-Up
This work follows studies conducted in the framework of the French research program MaCEnA (PIA), aiming to predict air leakage through a reinforced (and prestressed) concrete structure. As mentioned by the international Benchmark VeRCoRs, only very few teams were able to predict them and variations of at least one order of magnitude between participants were observed.
Reinforced concrete tightness estimation is of the utmost importance for confinement vessels but also to assess concrete structures durability. One of the reasons for these difficulties lies in the fact that air leakage prediction is the last step of complex, multiphysics and coupled simulations. On the one hand, to predict concrete permeability, saturation evolution of the porous network needs to be correctly addressed. On the other hand, cracks predictions (numbers, openings, and appearance time) is essential but not sufficient since roughnesses, tortuosities and connectivities of these latter also strongly influence the leakage rate.
After a first part showing the capacity of the used model to mimic the behavior of a structural representative volume, this contribution quantifies the effect of the use of autocorrelated random fields modelling the tensile strength on the concrete structural leakage prediction. The results highlight that the air leakage prediction can easily vary by one order of magnitude for the same random field parameters. Moreover, during mechanical loading, observation of the cracks evolutions (numbers, openings and positions) allows for quantifying the prevalence of material and structural heterogeneity and explains the sudden evolution of leakage rate.
Probabilistic Modelling of Containment Building Leakage at the Structural Scale: Application to the PACE Mock-Up
RILEM Bookseries
Rossi, Pierre (editor) / Tailhan, Jean-Louis (editor) / Briffaut, M. (author) / Ghannoum, M. (author) / Baroth, J. (author) / Cheikh Sleiman, H. (author) / Dufour, F. (author)
RILEM International Conference on Numerical Modeling Strategies for Sustainable Concrete Structures ; 2022 ; Marseille, France
Numerical Modeling Strategies for Sustainable Concrete Structures ; Chapter: 7 ; 69-78
RILEM Bookseries ; 38
2022-07-01
10 pages
Article/Chapter (Book)
Electronic Resource
English
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