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Record W3130871230 · doi:10.1680/jenge.20.00143

Simulation of water storage in a reclamation cover incorporating tailings consolidation

2021· article· en· W3130871230 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnvironmental Geotechnics · 2021
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTailingsConsolidation (business)Land reclamationEnvironmental scienceGeotechnical engineeringTailings damMining engineeringEngineeringMaterials science

Abstract

fetched live from OpenAlex

Successful reclamation of mine tailings requires effective management of the contaminated water generated by the consolidation of tailings over time. Due to uncertainty in predicting consolidation-induced water release, mine planners often use simulation models to prepare for a range of anticipated scenarios. This paper describes the development of the Tailings Management Simulation Consolidation model (TMSim-Consol) using the GoldSim software. TMSim-Consol simulates tailings settlement over time and the upward flow of pore water due to consolidation. The advantages of using system dynamics simulation tools are illustrated by the inherent transparency of the numerical method to end users. A hypothetical reclamation set-up consisting of an oil sands thickened tailings (OSTT) deposit capped by a sand layer was simulated under a range of initial tailings properties. The simulation results showed that soil water storage in the sand cap was highly sensitive to the initial solids contents of the underlying OSTT. To limit the release of contaminated water at the surface, the initial solids content of OSTT needs to be at least 65% before sand capping.

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.

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 score0.011
Threshold uncertainty score0.330

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 head0.007
GPT teacher head0.189
Teacher spread0.182 · 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