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Record W4205323640 · doi:10.22215/etd/2021-14653

Ultrasonic Interrogation of Oil Sands Tailings during Sedimentation

2021· dissertation· en· W4205323640 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

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsCarleton University
Fundersnot available
KeywordsTailingsOil sandsConsolidation (business)Land reclamationAttenuationGeotechnical engineeringUltrasonic sensorTailings damEnvironmental scienceGeologyPetroleum engineeringMaterials scienceAcousticsAsphaltGeographyComposite material

Abstract

fetched live from OpenAlex

Ultrasonic pulse velocity method is widely used to evaluate the quality of concrete. However, it has never been used to evaluate properties of oil sand tailings, which have poor consolidation properties, leading to continuous accumulation of tailings ponds, affecting the process of reclamation. The objective of this paper is to assess whether the UPV method can be an on-site measurement application in the oil sand tailings to make a rapid evaluation of tailings' properties over time. Equipment is calibrated, verified, and used to capture P-waves and S-waves when the waves interact with the column filled with flocculated fluid fine tailings. To increase reliability of the UPV test, special "holders" were designed to improve stabilization of transducers. Inferred wave velocities and changes in wave attenuation determined from p-wave data showed correlations with expected changes in density in the column; data using s-wave or p-wave-s-wave combinations did not show useful trends.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.627

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 head0.261
Teacher spread0.254 · 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

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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Same topicGeophysical Methods and ApplicationsFrench-language works237,207