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Record W2562750687 · doi:10.3390/min7010004

An Investigation of the Uniaxial Compressive Strength of a Cemented Hydraulic Backfill Made of Alluvial Sand

2017· article· en· W2562750687 on OpenAlexaffabout
Guangsheng Liu, Li Li, Mike Yao, David Landry, Farid Malek, Xiaocong Yang, Lijie Guo

Bibliographic record

VenueMinerals · 2017
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsVale (Canada)Polytechnique Montréal
Fundersnot available
KeywordsGeotechnical engineeringCompressive strengthGeologyShear (geology)DiagonalMaterials scienceComposite materialMathematics

Abstract

fetched live from OpenAlex

Backfill is commonly used in underground mines. The quality control of the backfill is a key step to ensure it meets the designed strength requirement. This is done through sample collection from the underground environment, followed by uniaxial compression tests to obtain the Uniaxial Compressive Strength (UCS) in the laboratory. When the cylindrical cemented backfill samples are axially loaded to failure, several failure modes can be observed and mainly classified into diagonal shear failure and axial split failure. To date, the UCS obtained by these two failure modes are considered to be the same with no distinction between them. In this paper, an analysis of the UCS results obtained on a cemented hydraulic backfill made of alluvial sand at a Canadian underground mine over the course of more than three years is presented. The results show that the UCS values obtained by diagonal shear failure are generally higher than those obtained by axial split failure for samples with the same recipe and curing time. This highlights the importance of making a distinction between the UCS values obtained by the two different modes of failure. Their difference in failure mechanism is explained. Further investigations on the sources of the data dispersion tend to indicate that the UCS obtained by laboratory tests following the current practice may not be representative of the in-situ strength distribution in the underground stopes due to segregation in cemented hydraulic backfill.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.032
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.227
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations33
Published2017
Admission routes2
Has abstractyes

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