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Record W2037095255 · doi:10.1139/e00-031

Predicted groundwater circulation in fractured and unfractured anisotropic porous media driven by nuclear fuel waste heatgeneration

2000· article· en· W2037095255 on OpenAlexaffvenueabout
Jianwen Yang, R. N. Edwards

Bibliographic record

VenueCanadian Journal of Earth Sciences · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsUniversity of Toronto
FundersAustralian Research Council
KeywordsBuoyancyGroundwaterFluid dynamicsNatural convectionPorous mediumGroundwater flowGeologyRadioactive wasteFlow (mathematics)Heat transferHydrogeologyPorosityPetroleum engineeringEnvironmental scienceMechanicsGeotechnical engineeringWaste managementAquiferEngineering

Abstract

fetched live from OpenAlex

The concept of nuclear fuel waste disposal underground is drawing increasing attention due to its many advantages against the current storage methods at surface. In this paper, we employ the Galerkin finite-element technique to solve the coupled time-dependent heat transfer and fluid flow differential equations and to predict the evolving behaviour of groundwater flow and subsurface temperature distribution associated witha proposed disposal system at the Whiteshell Research Area in southeastern Manitoba. A two-dimensional (2-D) numerical model is conceptualized from geologicalconstraints in this particular area. To investigate the free convection of groundwater flow driven by nuclear fuel waste heat generation, we assume the 2-D model has a flat upper boundary so as to eliminate the effect of topography head. Buoyancy force due to fluid density variationsis, therefore, the sole driving mechanism for fluid migration. Case studies for both unfractured and fractured porous media confirm that thermal decay of the buried fuel waste can initiate fluid circulation. In the presence of discrete fractures, the deep and hot fluid nearby the disposed contaminant can discharge to the biosphere, thus potentially threatening human health and the natural environment.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.999

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.188
Teacher spread0.180 · 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.

Study designObservational
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

Citations24
Published2000
Admission routes3
Has abstractyes

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