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  • 标题:Towards Bayesian Quantification of Permeability in Micro-scale Porous Structures – The Database of Micro Networks
  • 本地全文:下载
  • 作者:Babak Fazelabdolabadi ; Mohammad Hossein Golestan
  • 期刊名称:HighTech and Innovation Journal
  • 电子版ISSN:2723-9535
  • 出版年度:2020
  • 卷号:1
  • 期号:4
  • 页码:148-160
  • DOI:10.28991/HIJ-2020-01-04-02
  • 语种:English
  • 出版社:Ital Publication
  • 摘要:This article develops a Bayesian framework to quantify the absolute permeability of water in a porous structure from the geometry and clustering parameters of its underlying pore-throat network. These parameters include the network`s diameter, transivity, degree, centrality, assortativity, edge density, K-core decomposition, Kleinberg’s hub centrality scores, Kleinberg's authority centrality scores, length, and porosity. In addition, the incorporated clustering aspects of the networks have been determined with respect to several clustering criteria – edge betweenness, greedy optimization of modularity, multi-level optimization of modularity, and short random walks. As such, the article takes the first footsteps of creating a Database of Micro Networks for micro-scale porous structures, to be used as main input stream for the proposed Bayesian scheme.   Doi: 10.28991/HIJ-2020-01-04-02 Full Text: PDF
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