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Functional regression-based fluid permeability prediction in monodisperse sphere packings from isotropic two-point correlation functions
RISE - Research Institutes of Sweden, Biovetenskap och material, Jordbruk och livsmedel. Chalmers University of Technology, Sweden.ORCID-id: 0000-0002-5956-9934
RISE - Research Institutes of Sweden, Biovetenskap och material, Jordbruk och livsmedel.
RISE - Research Institutes of Sweden, Biovetenskap och material, Jordbruk och livsmedel. Chalmers University of Technology, Sweden.ORCID-id: 0000-0001-9979-5488
2017 (engelsk)Inngår i: Computational materials science, ISSN 0927-0256, E-ISSN 1879-0801, Vol. 134, s. 126-131Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

We study fluid permeability in random sphere packings consisting of impermeable monodisperse hard spheres. Several different pseudo-potential models are used to obtain varying degrees of microstructural heterogeneity. Systematically varying solid volume fraction and degree of heterogeneity, virtual screening of more than 10,000 material structures is performed, simulating fluid flow using a lattice Boltzmann framework and computing the permeability. We develop a well-performing functional regression model for permeability prediction based on using isotropic two-point correlation functions as microstructural descriptors. The performance is good over a large range of solid volume fractions and degrees of heterogeneity, and to our knowledge this is the first attempt at using two-point correlation functions as functional predictors in a nonparametric statistics/machine learning context for permeability prediction.

sted, utgiver, år, opplag, sider
2017. Vol. 134, s. 126-131
Emneord [en]
Correlation functions, Functional regression, Granular materials, Permeability, Sphere packings, Flow of fluids, Forecasting, Packing, Regression analysis, Spheres, Volume fraction, Correlation function, Microstructural descriptors, Microstructural heterogeneity, Non-parametric statistics, Permeability prediction, Two point correlation functions, Mechanical permeability
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Identifikatorer
URN: urn:nbn:se:ri:diva-30877DOI: 10.1016/j.commatsci.2017.03.042Scopus ID: 2-s2.0-85017093852OAI: oai:DiVA.org:ri-30877DiVA, id: diva2:1139010
Tilgjengelig fra: 2017-09-06 Laget: 2017-09-06 Sist oppdatert: 2018-08-17bibliografisk kontrollert

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