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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Steenackers, Gunther
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Publications (4/4 displayed)
- 2024Combined macro X-ray fluorescence (MA-XRF) and pulse phase thermography (PPT) imaging for the technical study of panel paintingscitations
- 2021Permeability of cementitious materials using a multiscale pore network modelcitations
- 2020A multiscale framework to estimate water sorption isotherms for OPC-based materialscitations
- 2016Development of an equivalent composite honeycomb modelcitations
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article
A multiscale framework to estimate water sorption isotherms for OPC-based materials
Abstract
This paper presents a new multiscale framework to estimate water sorption isotherms (WSI) for ordinary Portland cement (OPC) based materials. This is achieved by integrating: (i) particle packing, (ii) cement hydration kinetics, and (iii) pore network models. The first two models provide pore size distribution for gel and capillary pores. The pore network model takes these as inputs to construct an idealized network of pores connected by so called throats. By invoking appropriate thermodynamic equilibrium laws for the adsorbed and capillary water locally and using an existing percolation algorithm, WSI are estimated via a series of steady-state analysis. A notable feature of the proposed framework is that there is only one geometrical calibration parameter needed in the pore network model, excluding calibration inherent in the cement hydration kinetics model. The capability of the framework is demonstrated by comparing the model predictions with eleven independent experimentally determined WSI, in particular, desorption isotherms. It is shown that the model is able to estimate WSI with coefficient of determination (R2) value being 0.85 or above for all the cases.