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Record W4408029155 · doi:10.1016/j.powtec.2025.120834

Investigation of crack self-healing behaviour and its impact on strength and permeability recovery in cemented paste tailings

2025· article· en· W4408029155 on OpenAlexafffund
Weizhou Quan, Mamadou Fall

Bibliographic record

VenuePowder Technology · 2025
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Ottawa
KeywordsTailingsPermeability (electromagnetism)Materials scienceGeotechnical engineeringSelf-healingComposite materialEngineeringMetallurgyChemistryMembrane

Abstract

fetched live from OpenAlex

Cemented paste backfill (an engineered mixture of tailings, binder, and water), as one of the sustainable technological innovations for mining waste management, is used extensively around the world as a cementitious construction material in underground mines. The induced cracks within the CPB material tend to severely weaken the integrity and mechanical strength of the CPB structures as well as increase their permeability properties, undermining their safety, serviceability, durability, and environmental performance. However, no studies have been conducted to investigate the autogenous self-healing capability and behaviour of CPB. Therefore, this paper presents the results of an experimental study on the autogenous healing behaviour in CPB material to understand the self-healing mechanism and evaluate the self-healing efficiency through the recovery of mechanical and permeation properties. To this end, the CPB specimens were pre-damaged at different initial curing periods (i.e., 3, 7, and 28 days) and at different pre-damage levels (i.e., 30 %, 50 %, 75 %, 90 %, or 100 % of ultimate compressive strength in the pre-peak phase); then cured with self-healing periods of 1, 7, 28 or 90 days. Mechanical and hydraulic conductivity tests were performed on the pre-damaged specimens to monitor the self-healing changes. The results demonstrate that a significant self-healing capability does exist in the CPB materials due to the formed self-healing products from continuous cement hydration interior of the CPB matrix and carbonation of calcium hydroxide. The mechanical strength and hydraulic conductivity of pre-damaged specimens can be restored to similar values of the control specimens after 7 days and 28 days of self-healing periods, respectively. Furthermore, the study also reveals that the CPB specimens with high pre-damage levels (i.e., 75 %, 90 %, or 100 %) can even achieve up to 42 % higher mechanical strengths than the control specimens after 90 days of the self-healing period, indicating that the initiated cracks within the CPB matrix can ameliorate the hydration reactions favoring the self-healing performance. The results presented in the paper would have significant impacts and practical implications with respect to CPB structure design, mechanical stability, and durability. • Crack self-healing ability of cemented paste backfill (CPB) studied. • Impact of self-healing on strength and permeability recovery assessed. • CPB shows significant self-healing capability. • Mechanical strength and hydraulic conductivity of pre-damaged CPBs restored.

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)0.000
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.009
GPT teacher head0.228
Teacher spread0.219 · 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".

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Citations7
Published2025
Admission routes2
Has abstractyes

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