MétaCan
Menu
Back to cohort
Record W2094172293 · doi:10.1139/t07-016

Experimental and numerical analysis of desiccation of a mining waste

2007· article· en· W2094172293 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Geotechnical Journal · 2007
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
Fundersnot available
KeywordsDesiccationTailingsGeotechnical engineeringCrackingSoil waterHydraulic conductivityComputer simulationNumerical analysisProcess (computing)Ultimate tensile strengthCharacterization (materials science)Environmental scienceEngineeringMaterials scienceComputer scienceMathematicsSoil scienceMetallurgySimulationEcologyComposite material

Abstract

fetched live from OpenAlex

The paper presents an analysis of the desiccation process in mining materials, based on physical laws. Due to the process complexity, most of the previous approaches used have an empirical basis. In this case, however, a formulation using coupled hydromechanical equations has been considered. To show the capabilities of the theoretical framework, several laboratory tests were performed, and afterwards a numerical simulation of the measured variables was attempted. The material tested was a metallurgical waste in tailings form and it was exposed to atmospheric desiccation. Further cracking will eventually change its properties, and this may have an environmental impact. Some of the experiments were devoted to material characterization, including the water retention curve, the hydraulic conductivity, and the tensile strength. In addition, laboratory drying tests open to the atmosphere or in hermetically closed containers were also performed. The numerical analyses carried out attempted to simulate some of these tests. One of the main outcomes of the analyses was the prediction of the time and the location of crack initiation. Finally, it should be pointed out that good agreement between the experiments and numerical simulations indicates that the formulation is taking into account the fundamental mechanisms involved in the desiccation process.Key words: desiccation, drying cracks, unsaturated soils, waste material, coupled phenomena, modelling.

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 score0.290
Threshold uncertainty score0.259

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.222
Teacher spread0.212 · 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