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Record W2996982759 · doi:10.3390/min10010032

A Mathematical Model of Gas and Water Flow in a Swelling Geomaterial—Part 2. Process Simulation

2019· article· en· W2996982759 on OpenAlexafffund
Elias Ernest Dagher, Julio Ángel Infante Sedano, T.S. Nguyen

Bibliographic record

VenueMinerals · 2019
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsUniversity of OttawaCanadian Nuclear Safety Commission
FundersCanadian Nuclear Safety CommissionEidgenössisches NuklearsicherheitsinspektoratInstitut de Radioprotection et de SÛreté NucléaireKorea Atomic Energy Research InstituteJapan Atomic Energy AgencyNuclear Waste Management OrganizationU.S. Department of Energy
KeywordsPoromechanicsGeotechnical engineeringContainment (computer programming)Radioactive wastePetroleum engineeringEnvironmental scienceFlow (mathematics)Darcy's lawPorous mediumPermeability (electromagnetism)PorosityMechanicsMaterials scienceGeologyWaste managementEngineeringComputer scienceChemistry

Abstract

fetched live from OpenAlex

Gases can potentially generate in a deep geological repository (DGR) for the long-term containment of radioactive waste. Natural and engineered barriers provide containment of the waste by mitigating contaminant migration. However, if gas pressures exceed the mechanical strength of these barriers, preferential flow pathways for both the gases and the porewater could form, providing a source of potential exposure to people and the environment. Expansive soils, such as bentonite-based materials, are widely considered as sealing materials. Understanding the long-term performance of these seals as barriers against gas migration is an important component in the design and the long-term safety assessment of a DGR. This study proposes a hydro-mechanical mathematical model for migration of gas through a low-permeable swelling geomaterial based on the theoretical framework of poromechanics. Using the finite element method, the model is used to simulate 1D flow through a confined cylindrical sample of near-saturated low-permeable soil under a constant volume boundary stress condition. The study expands upon previous work by the authors by assessing the influence of heterogeneity, the Klinkenberg “slip flow” effect, and a swelling stress on flow behavior. Based on the results, this study provides fundamental insight into a number of factors that may influence two-phase flow.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.232

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.220
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2019
Admission routes2
Has abstractyes

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