Multi-Scale Computational Methods for Reactive Transport of in situ Uranium Leaching: Pore Structure Evolution, Multi-Physics Coupling, and Numerical Simulations.
Saved in:
| Title: | Multi-Scale Computational Methods for Reactive Transport of in situ Uranium Leaching: Pore Structure Evolution, Multi-Physics Coupling, and Numerical Simulations. |
|---|---|
| Authors: | Hou, Shanshan1 (AUTHOR), Zeng, Sheng1 (AUTHOR) usczengs@126.com, Yang, Yugui2 (AUTHOR), Song, Jiayin1 (AUTHOR), Sun, Bing3 (AUTHOR) |
| Source: | Archives of Computational Methods in Engineering. Sep2026, Vol. 33 Issue 7, p9475-9520. 46p. |
| Subjects: | Multiscale modeling, Reactive flow, Porosity, Artificial intelligence, Computer simulation, Dissolution (Chemistry), Leaching |
| Abstract: | In situ leaching (ISL) uranium mining involves intricate multi-scale dynamics spanning nine orders of magnitude, multi-physics coupling among hydraulic, transport, chemical, thermal, and mechanical fields, as well as strong nonlinearity arising from dissolution-precipitation feedback. This review systematically examines recent advances in three fundamental aspects of ISL uranium mining: characterization and evolution of porous media structures, multi-physics coupling mechanisms, and numerical simulation of reactive transport processes. Methodologies for pore structure characterization are outlined, dual fractal characteristics and their relationships with permeability are analyzed, and mechanisms governing pore evolution including dissolution-precipitation competition, particle migration, clay swelling, and gas blockage are elucidated. Seepage theories for multiple flow regimes are reviewed, reactive transport coupling models integrating five physical fields are examined, and reaction kinetics including rate laws, Arrhenius temperature dependence, and sorption models are summarized with dimensionless parameters characterizing dominant transport mechanisms. Multi-scale modeling approaches from pore-scale to field-scale are compared, major simulation platforms are evaluated with model selection criteria, and cross-scale correlation techniques including the embedded multi-scale method are discussed. Additionally, emerging applications of artificial intelligence technologies including machine learning surrogates, deep learning, physics-informed neural networks, and digital twins are highlighted for process optimization and environmental monitoring. Finally, key technical challenges and future research directions are identified. [ABSTRACT FROM AUTHOR] |
| Copyright of Archives of Computational Methods in Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 197451705 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Multi-Scale Computational Methods for Reactive Transport of in situ Uranium Leaching: Pore Structure Evolution, Multi-Physics Coupling, and Numerical Simulations. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Hou%2C+Shanshan%22">Hou, Shanshan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zeng%2C+Sheng%22">Zeng, Sheng</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> usczengs@126.com</i><br /><searchLink fieldCode="AR" term="%22Yang%2C+Yugui%22">Yang, Yugui</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Song%2C+Jiayin%22">Song, Jiayin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sun%2C+Bing%22">Sun, Bing</searchLink><relatesTo>3</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Archives+of+Computational+Methods+in+Engineering%22">Archives of Computational Methods in Engineering</searchLink>. Sep2026, Vol. 33 Issue 7, p9475-9520. 46p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Multiscale+modeling%22">Multiscale modeling</searchLink><br /><searchLink fieldCode="DE" term="%22Reactive+flow%22">Reactive flow</searchLink><br /><searchLink fieldCode="DE" term="%22Porosity%22">Porosity</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+simulation%22">Computer simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Dissolution+%28Chemistry%29%22">Dissolution (Chemistry)</searchLink><br /><searchLink fieldCode="DE" term="%22Leaching%22">Leaching</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In situ leaching (ISL) uranium mining involves intricate multi-scale dynamics spanning nine orders of magnitude, multi-physics coupling among hydraulic, transport, chemical, thermal, and mechanical fields, as well as strong nonlinearity arising from dissolution-precipitation feedback. This review systematically examines recent advances in three fundamental aspects of ISL uranium mining: characterization and evolution of porous media structures, multi-physics coupling mechanisms, and numerical simulation of reactive transport processes. Methodologies for pore structure characterization are outlined, dual fractal characteristics and their relationships with permeability are analyzed, and mechanisms governing pore evolution including dissolution-precipitation competition, particle migration, clay swelling, and gas blockage are elucidated. Seepage theories for multiple flow regimes are reviewed, reactive transport coupling models integrating five physical fields are examined, and reaction kinetics including rate laws, Arrhenius temperature dependence, and sorption models are summarized with dimensionless parameters characterizing dominant transport mechanisms. Multi-scale modeling approaches from pore-scale to field-scale are compared, major simulation platforms are evaluated with model selection criteria, and cross-scale correlation techniques including the embedded multi-scale method are discussed. Additionally, emerging applications of artificial intelligence technologies including machine learning surrogates, deep learning, physics-informed neural networks, and digital twins are highlighted for process optimization and environmental monitoring. Finally, key technical challenges and future research directions are identified. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Archives of Computational Methods in Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=197451705 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11831-026-10519-5 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 46 StartPage: 9475 Subjects: – SubjectFull: Multiscale modeling Type: general – SubjectFull: Reactive flow Type: general – SubjectFull: Porosity Type: general – SubjectFull: Artificial intelligence Type: general – SubjectFull: Computer simulation Type: general – SubjectFull: Dissolution (Chemistry) Type: general – SubjectFull: Leaching Type: general Titles: – TitleFull: Multi-Scale Computational Methods for Reactive Transport of in situ Uranium Leaching: Pore Structure Evolution, Multi-Physics Coupling, and Numerical Simulations. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Hou, Shanshan – PersonEntity: Name: NameFull: Zeng, Sheng – PersonEntity: Name: NameFull: Yang, Yugui – PersonEntity: Name: NameFull: Song, Jiayin – PersonEntity: Name: NameFull: Sun, Bing IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 11343060 Numbering: – Type: volume Value: 33 – Type: issue Value: 7 Titles: – TitleFull: Archives of Computational Methods in Engineering Type: main |
| ResultId | 1 |
