Flow estimation solely from image data through persistent homology analysis

Abstract Topological data analysis is an emerging concept of data analysis for characterizing shapes. A state-of-the-art tool in topological data analysis is persistent homology, which is expected to summarize quantified topological and geometric features. Although persistent homology is useful for...

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Autores principales:	Anna Suzuki, Miyuki Miyazawa, James M. Minto, Takeshi Tsuji, Ippei Obayashi, Yasuaki Hiraoka, Takatoshi Ito
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/eaafc9772d084cb9aa067308edc1c1ac
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id	oai:doaj.org-article:eaafc9772d084cb9aa067308edc1c1ac
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spelling	oai:doaj.org-article:eaafc9772d084cb9aa067308edc1c1ac2021-12-02T17:41:12ZFlow estimation solely from image data through persistent homology analysis10.1038/s41598-021-97222-62045-2322https://doaj.org/article/eaafc9772d084cb9aa067308edc1c1ac2021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-97222-6https://doaj.org/toc/2045-2322Abstract Topological data analysis is an emerging concept of data analysis for characterizing shapes. A state-of-the-art tool in topological data analysis is persistent homology, which is expected to summarize quantified topological and geometric features. Although persistent homology is useful for revealing the topological and geometric information, it is difficult to interpret the parameters of persistent homology themselves and difficult to directly relate the parameters to physical properties. In this study, we focus on connectivity and apertures of flow channels detected from persistent homology analysis. We propose a method to estimate permeability in fracture networks from parameters of persistent homology. Synthetic 3D fracture network patterns and their direct flow simulations are used for the validation. The results suggest that the persistent homology can estimate fluid flow in fracture network based on the image data. This method can easily derive the flow phenomena based on the information of the structure.Anna SuzukiMiyuki MiyazawaJames M. MintoTakeshi TsujiIppei ObayashiYasuaki HiraokaTakatoshi ItoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Anna Suzuki Miyuki Miyazawa James M. Minto Takeshi Tsuji Ippei Obayashi Yasuaki Hiraoka Takatoshi Ito Flow estimation solely from image data through persistent homology analysis
description	Abstract Topological data analysis is an emerging concept of data analysis for characterizing shapes. A state-of-the-art tool in topological data analysis is persistent homology, which is expected to summarize quantified topological and geometric features. Although persistent homology is useful for revealing the topological and geometric information, it is difficult to interpret the parameters of persistent homology themselves and difficult to directly relate the parameters to physical properties. In this study, we focus on connectivity and apertures of flow channels detected from persistent homology analysis. We propose a method to estimate permeability in fracture networks from parameters of persistent homology. Synthetic 3D fracture network patterns and their direct flow simulations are used for the validation. The results suggest that the persistent homology can estimate fluid flow in fracture network based on the image data. This method can easily derive the flow phenomena based on the information of the structure.
format	article
author	Anna Suzuki Miyuki Miyazawa James M. Minto Takeshi Tsuji Ippei Obayashi Yasuaki Hiraoka Takatoshi Ito
author_facet	Anna Suzuki Miyuki Miyazawa James M. Minto Takeshi Tsuji Ippei Obayashi Yasuaki Hiraoka Takatoshi Ito
author_sort	Anna Suzuki
title	Flow estimation solely from image data through persistent homology analysis
title_short	Flow estimation solely from image data through persistent homology analysis
title_full	Flow estimation solely from image data through persistent homology analysis
title_fullStr	Flow estimation solely from image data through persistent homology analysis
title_full_unstemmed	Flow estimation solely from image data through persistent homology analysis
title_sort	flow estimation solely from image data through persistent homology analysis
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/eaafc9772d084cb9aa067308edc1c1ac
work_keys_str_mv	AT annasuzuki flowestimationsolelyfromimagedatathroughpersistenthomologyanalysis AT miyukimiyazawa flowestimationsolelyfromimagedatathroughpersistenthomologyanalysis AT jamesmminto flowestimationsolelyfromimagedatathroughpersistenthomologyanalysis AT takeshitsuji flowestimationsolelyfromimagedatathroughpersistenthomologyanalysis AT ippeiobayashi flowestimationsolelyfromimagedatathroughpersistenthomologyanalysis AT yasuakihiraoka flowestimationsolelyfromimagedatathroughpersistenthomologyanalysis AT takatoshiito flowestimationsolelyfromimagedatathroughpersistenthomologyanalysis
_version_	1718379737440583680

Flow estimation solely from image data through persistent homology analysis

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