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Record W4405736601 · doi:10.3390/min15010004

A New Yield Surface for Cemented Paste Backfill Based on the Modified Structured Cam-Clay

2024· article· en· W4405736601 on OpenAlexaff
A. Safari, Abbas Taheri, Murat Karakus

Bibliographic record

VenueMinerals · 2024
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsQueen's University
Fundersnot available
KeywordsYield (engineering)Materials scienceGeotechnical engineeringGeologyComposite material

Abstract

fetched live from OpenAlex

Cemented paste backfill (CPB) is a cemented void filling method gaining popularity over traditional hydraulic or rockfill methods. As mining depth increases, CPB-filled stopes are subjected to higher confining pressures. Due to the soil triaxial apparatus limitations, as the conventional method of triaxial testing on CPB, no confining pressures higher than 5 MPa can be applied to CPB over a range of curing time. This lack of data introduces uncertainty in predicting CPB behavior, potentially leading to an overestimation of the required strength. To address this, this study introduces a new testing method that allows for higher confinement beyond traditional limitations by modifying the Hoek triaxial cell to accommodate low-strength materials. This study then investigates the coupled influence of confining pressure and curing time (hydration) on CPB characteristics, specifically examining the impacts of different curing times and confining pressures on the mechanical and rheological properties of CPB. A total of 75 triaxial tests were conducted using 42 mm cylinder shape samples at five various curing times from 7 to 96 days, and applied at low and high confinement condition levels (0.5 to 30 MPa). The results reveal that hydration and confinement positively impact the CPB strength. The modified structured Cam-Clay model was selected to predict the behavior, and its yield surface was updated using the experimental results. The proposed yield model can be utilized to describe CPB material subjected to various curing and pressure conditions underground.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.430
Threshold uncertainty score0.557

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)0.0010.000

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 head0.032
GPT teacher head0.221
Teacher spread0.189 · 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.

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

Citations5
Published2024
Admission routes1
Has abstractyes

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