Transient Electromagnetic Monitoring of Permafrost: Mathematical Modeling Based on Sumudu Integral Transform and Artificial Neural Networks
Due to the ongoing global warming on the Earth, permafrost degradation has been extensively taking place, which poses a substantial threat to civil and industrial facilities and infrastructure elements, as well as to the utilization of natural resources in the Arctic and high-latitude regions. In or...
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2024
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ftdoajarticles:oai:doaj.org/article:c6339707bb194c78ab1290eb60305df1 2024-09-15T18:08:08+00:00 Transient Electromagnetic Monitoring of Permafrost: Mathematical Modeling Based on Sumudu Integral Transform and Artificial Neural Networks Viacheslav Glinskikh Oleg Nechaev Igor Mikhaylov Marina Nikitenko Kirill Danilovskiy 2024-02-01T00:00:00Z https://doi.org/10.3390/math12040585 https://doaj.org/article/c6339707bb194c78ab1290eb60305df1 EN eng MDPI AG https://www.mdpi.com/2227-7390/12/4/585 https://doaj.org/toc/2227-7390 doi:10.3390/math12040585 2227-7390 https://doaj.org/article/c6339707bb194c78ab1290eb60305df1 Mathematics, Vol 12, Iss 4, p 585 (2024) permafrost TEM monitoring Sumudu transform vector finite element method artificial neural networks Mathematics QA1-939 article 2024 ftdoajarticles https://doi.org/10.3390/math12040585 2024-08-05T17:49:58Z Due to the ongoing global warming on the Earth, permafrost degradation has been extensively taking place, which poses a substantial threat to civil and industrial facilities and infrastructure elements, as well as to the utilization of natural resources in the Arctic and high-latitude regions. In order to prevent the negative consequences of permafrost thawing under the foundations of constructions, various geophysical techniques for monitoring permafrost have been proposed and applied so far: temperature, electrical, seismic and many others. We propose a cross-borehole exploration system for a high localization of target objects in the cryolithozone. A novel mathematical apparatus for three-dimensional modeling of transient electromagnetic signals by the vector finite element method has been developed. The original combination of the latter, the Sumudu integral transform and artificial neural networks makes it possible to examine spatially heterogeneous objects of the cryolithozone with a high contrast of geoelectric parameters, significantly reducing computational costs. We consider numerical simulation results of the transient electromagnetic monitoring of industrial facilities located on permafrost. The formation of a talik has been shown to significantly manifest itself in the measured electromagnetic responses, which enables timely prevention of industrial disasters and environmental catastrophes. Article in Journal/Newspaper Global warming permafrost Directory of Open Access Journals: DOAJ Articles Mathematics 12 4 585 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English |
topic |
permafrost TEM monitoring Sumudu transform vector finite element method artificial neural networks Mathematics QA1-939 |
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permafrost TEM monitoring Sumudu transform vector finite element method artificial neural networks Mathematics QA1-939 Viacheslav Glinskikh Oleg Nechaev Igor Mikhaylov Marina Nikitenko Kirill Danilovskiy Transient Electromagnetic Monitoring of Permafrost: Mathematical Modeling Based on Sumudu Integral Transform and Artificial Neural Networks |
topic_facet |
permafrost TEM monitoring Sumudu transform vector finite element method artificial neural networks Mathematics QA1-939 |
description |
Due to the ongoing global warming on the Earth, permafrost degradation has been extensively taking place, which poses a substantial threat to civil and industrial facilities and infrastructure elements, as well as to the utilization of natural resources in the Arctic and high-latitude regions. In order to prevent the negative consequences of permafrost thawing under the foundations of constructions, various geophysical techniques for monitoring permafrost have been proposed and applied so far: temperature, electrical, seismic and many others. We propose a cross-borehole exploration system for a high localization of target objects in the cryolithozone. A novel mathematical apparatus for three-dimensional modeling of transient electromagnetic signals by the vector finite element method has been developed. The original combination of the latter, the Sumudu integral transform and artificial neural networks makes it possible to examine spatially heterogeneous objects of the cryolithozone with a high contrast of geoelectric parameters, significantly reducing computational costs. We consider numerical simulation results of the transient electromagnetic monitoring of industrial facilities located on permafrost. The formation of a talik has been shown to significantly manifest itself in the measured electromagnetic responses, which enables timely prevention of industrial disasters and environmental catastrophes. |
format |
Article in Journal/Newspaper |
author |
Viacheslav Glinskikh Oleg Nechaev Igor Mikhaylov Marina Nikitenko Kirill Danilovskiy |
author_facet |
Viacheslav Glinskikh Oleg Nechaev Igor Mikhaylov Marina Nikitenko Kirill Danilovskiy |
author_sort |
Viacheslav Glinskikh |
title |
Transient Electromagnetic Monitoring of Permafrost: Mathematical Modeling Based on Sumudu Integral Transform and Artificial Neural Networks |
title_short |
Transient Electromagnetic Monitoring of Permafrost: Mathematical Modeling Based on Sumudu Integral Transform and Artificial Neural Networks |
title_full |
Transient Electromagnetic Monitoring of Permafrost: Mathematical Modeling Based on Sumudu Integral Transform and Artificial Neural Networks |
title_fullStr |
Transient Electromagnetic Monitoring of Permafrost: Mathematical Modeling Based on Sumudu Integral Transform and Artificial Neural Networks |
title_full_unstemmed |
Transient Electromagnetic Monitoring of Permafrost: Mathematical Modeling Based on Sumudu Integral Transform and Artificial Neural Networks |
title_sort |
transient electromagnetic monitoring of permafrost: mathematical modeling based on sumudu integral transform and artificial neural networks |
publisher |
MDPI AG |
publishDate |
2024 |
url |
https://doi.org/10.3390/math12040585 https://doaj.org/article/c6339707bb194c78ab1290eb60305df1 |
genre |
Global warming permafrost |
genre_facet |
Global warming permafrost |
op_source |
Mathematics, Vol 12, Iss 4, p 585 (2024) |
op_relation |
https://www.mdpi.com/2227-7390/12/4/585 https://doaj.org/toc/2227-7390 doi:10.3390/math12040585 2227-7390 https://doaj.org/article/c6339707bb194c78ab1290eb60305df1 |
op_doi |
https://doi.org/10.3390/math12040585 |
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Mathematics |
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12 |
container_issue |
4 |
container_start_page |
585 |
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1810445482060677120 |