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Record W4406846294 · doi:10.3390/min15020123

Mechanical and Microstructural Behavior of Cemented Paste Backfill Under Cyclic Loading

2025· article· en· W4406846294 on OpenAlexaff
A. Safari, Abbas Taheri, Murat Karakus

Bibliographic record

VenueMinerals · 2025
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsQueen's University
FundersAustralian Government
KeywordsMaterials scienceGeotechnical engineeringComposite materialMetallurgyGeology

Abstract

fetched live from OpenAlex

Understanding the mechanical and physical behavior of aged CPB under cyclic loading is a significant area of research. Many parameters such as cementation (hydration) and the microstructure, which dictate the arrangement of particles and permeability, affect the mechanical features of cemented paste backfill (CPB). The impact of a wide range of external energy sources within the mining environment, such as cyclic loading resulting from long-term blasting, can significantly alter the applied stresses on the backfill mass. This paper aims to delve into this crucial area of research. A series of uniaxial cyclic tests were conducted on CPB, utilizing samples made from tailing materials sourced from a copper mine in South Australia. Different loading levels were applied at various curing times. All samples exhibited cyclic loading hardening behavior for cyclic loading levels between 80% and 93% of monotonic unconfined compressive strength (UCS), and a cyclic loading damage behavior was observed for 96% of UCS loading level for both 14- and 28-day curing periods. To further investigate these findings, scanning electron microscope analysis as well as sonic velocity tests were conducted for capturing microstructural changes in the samples before and after tests. These findings can be used to indicate a safe firing distance to a filled mass.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.332

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 head0.013
GPT teacher head0.227
Teacher spread0.214 · 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 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

Citations5
Published2025
Admission routes1
Has abstractyes

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