| Abstrakt: |
In a pore network model, microscopic moisture storage and transport processes are modeled at pore level after which this information is extrapolated to obtain macroscopic properties describing the material's moisture behavior. Such a model is typically validated by comparing measured and simulated macroscopic properties. However, due to the uncertainty associated with the experimental property determination, a possibly incorrect description of the model's microscopic processes can be overlooked. Assessing the model's ability to correctly simulate the moisture behavior at pore level is therefore required for its complete validation. To this aim, the moisture stored in the individual pores of unsaturated materials is imaged with the help of X-ray computed tomography images and compared to the moisture distribution simulated with a pore network model. The acquired X-ray computed tomography images clearly show the evolution of the drying process, wherein emptied pores retain water in their irregularly shaped corners. While some corners do not store any moisture, others allow a maximum of 10 % of the pore's volume to be filled with corner islands. By comparing these images with the pore network model, however, it becomes clear that the amount of water, trapped in these pore corners is heavily overestimated in the model's current implementation. Since this implementation is commonly used in existing pore network models, this paper proves the need of a detailed investigation of the corner islands in real porous media to formulate a different way of calculating moisture storage in pore corners. Article Highlights: Visualising the distribution of moisture in unsaturated material using X-ray computed tomography Microscopic validation of a pore network model by comparing the simulated moisture storage in the individual pore bodies and throats with X-ray computed tomography images of unsaturated material. Proof of the limitations of the pore network model with regards to moisture storage in pore corners and recommendations for possible model improvement. [ABSTRACT FROM AUTHOR] |
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