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A platform for research: civil engineering, architecture and urbanism
Network analysis of heat transfer in sands
https://orcid.org/0000-0002-9275-8403
https://orcid.org/0000-0003-1219-5661
Abstract Differences in the effective thermal conductivity (ETC) between measurements and models may be attributed to the limited ability to capture microstructural information of geomaterials. Today, computed tomography (CT) technology offers unprecedented access to such information, particularly for sands. Since a sand can be represented as a contact network made of nodes (particles) connected by edges (contacts), features (or variables) arising from the contact network can characterise particle connectivity. However, existing contact network features neglect the contribution of contact quality and of small gaps between neighbouring particles to heat transfer. To redress these issues, this paper introduces new weighted contact network features by considering contact area at each edge in the contact network. Additionally, thermal network features are proposed by considering small gaps as edges with/without being weighted by thermal conductance. All network features are calculated based on CT images of five real sands. The relationships between each feature and ETC are investigated. The results show that some network features that account for both the particle connectivity and contact quality can be used to predict ETC accurately. Advantages and limitations of this approach are also identified.
Network analysis of heat transfer in sands
https://orcid.org/0000-0002-9275-8403
https://orcid.org/0000-0003-1219-5661
Abstract Differences in the effective thermal conductivity (ETC) between measurements and models may be attributed to the limited ability to capture microstructural information of geomaterials. Today, computed tomography (CT) technology offers unprecedented access to such information, particularly for sands. Since a sand can be represented as a contact network made of nodes (particles) connected by edges (contacts), features (or variables) arising from the contact network can characterise particle connectivity. However, existing contact network features neglect the contribution of contact quality and of small gaps between neighbouring particles to heat transfer. To redress these issues, this paper introduces new weighted contact network features by considering contact area at each edge in the contact network. Additionally, thermal network features are proposed by considering small gaps as edges with/without being weighted by thermal conductance. All network features are calculated based on CT images of five real sands. The relationships between each feature and ETC are investigated. The results show that some network features that account for both the particle connectivity and contact quality can be used to predict ETC accurately. Advantages and limitations of this approach are also identified.
Network analysis of heat transfer in sands
https://orcid.org/0000-0002-9275-8403
https://orcid.org/0000-0003-1219-5661
Abstract Differences in the effective thermal conductivity (ETC) between measurements and models may be attributed to the limited ability to capture microstructural information of geomaterials. Today, computed tomography (CT) technology offers unprecedented access to such information, particularly for sands. Since a sand can be represented as a contact network made of nodes (particles) connected by edges (contacts), features (or variables) arising from the contact network can characterise particle connectivity. However, existing contact network features neglect the contribution of contact quality and of small gaps between neighbouring particles to heat transfer. To redress these issues, this paper introduces new weighted contact network features by considering contact area at each edge in the contact network. Additionally, thermal network features are proposed by considering small gaps as edges with/without being weighted by thermal conductance. All network features are calculated based on CT images of five real sands. The relationships between each feature and ETC are investigated. The results show that some network features that account for both the particle connectivity and contact quality can be used to predict ETC accurately. Advantages and limitations of this approach are also identified.
Network analysis of heat transfer in sands
Fei, Wenbin (author) / Narsilio, Guillermo A. (author)
2020-07-28
Article (Journal)
Electronic Resource
English
Network analysis of heat transfer in sands
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