Predicting permeability via statistical descriptors of morphology on polydisperse foams including membranes - Archive ouverte HAL
Communication Dans Un Congrès Année : 2021

Predicting permeability via statistical descriptors of morphology on polydisperse foams including membranes

Vincent Langlois
Johann Guilleminot
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Arnaud Duval
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Résumé

Quantitative structure-property relationships are crucial for the understanding and prediction of the acoustical properties of complex foams. For fluid flow in polydisperse foams, characterizing the pore size distribution and membrane content facilitates prediction of permeability, a key property that has been extensively studied in material science, geophysics and chemical engineering. In this work, we propose a formula to predict the permeability of polydisperse foams including membranes via microstructural descriptors which can be derived from X-ray microtomography and scanning electron micrographs.
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Dates et versions

hal-04129591 , version 1 (15-06-2023)

Identifiants

  • HAL Id : hal-04129591 , version 1

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Cong Truc Nguyen, Vincent Langlois, Johann Guilleminot, Fabrice Detrez, Arnaud Duval, et al.. Predicting permeability via statistical descriptors of morphology on polydisperse foams including membranes. The 11th edition of the Automotive NVH Comfort congress, Oct 2021, Le Mans (Sarthe), France. ⟨hal-04129591⟩
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