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Pore pressure dynamics in early-age cemented fill under multiaxial stress conditions

2025· article· en· W4414675843 on OpenAlexafffund
Hongbin Liu, Mamadou Fall

Bibliographic record

VenueCement and Concrete Composites · 2025
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship CouncilUniversity of Ottawa
KeywordsPore water pressureDrainageCuring (chemistry)InflowStress (linguistics)Closure (psychology)Water pressure

Abstract

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In deep underground mines, cemented paste backfill (CPB) is subjected to complex multiaxial stress conditions, including vertical self-loading and horizontal rockwall closure, which can significantly influence the evolution of pore water pressure (PWP). Understanding PWP development under these conditions is essential for ensuring barricade stability and the long-term performance of CPB structures. This study investigates the development of PWP in CPB under realistic deep mine conditions, particularly focusing on multiaxial stress loading and drainage availability. A novel multiaxial stress curing and monitoring apparatus was employed to simulate these coupled conditions and comprehensively capture the evolution of both positive and negative PWP within CPB throughout a 28-day curing period. Although the apparatus can impose field-like temperature histories and drainage boundaries, the present tests fix temperature to isolate mechanical and drainage effects. Groundwater inflow is not explicitly simulated; instead, controlled drainage boundaries are employed to bracket typical deep-mine backfill drainage conditions. Results indicate that horizontal rockwall closure stress significantly amplifies the magnitude and prolongs the duration of positive PWP by actively confining and entrapping pore water, resulting in notably higher peak PWP values and stress-induced pore pressure coefficients (C n ) compared to CPB subjected solely to vertical stress. Practically, this means that even at the same filling rate, CPB material subjected to additional horizontal rockwall closure in deep mines can experience significantly higher positive PWP, thereby increasing the load exerted on barricades at early curing stages and elevating the risk of barricade failure. As curing progresses and positive PWP dissipates, it eventually drops below zero, leading to the development of negative PWP (suction). To interpret this suction development, the study adopts the concept of the air-water interface (meniscus) from unsaturated soil mechanics, illustrating how curing-induced changes in pore structure influence meniscus curvature and consequently affect suction magnitude. Horizontal closure stress promotes consolidation and densification of CPB – supported by mercury intrusion porosimetry (MIP) and thermogravimetric (TG) analyses – which reduces pore size and enhances pore water consumption. This densification leads to smaller pore sizes, generating menisci with smaller radii of curvature, thereby increasing suction (negative PWP). However, rapid and high-magnitude horizontal stresses (rockwall closure 2) at later curing stages can induce a “resaturation effect,” partially reversing this beneficial suction increase, whereas moderate horizontal closure stress (rockwall closure 1) allows stable suction development throughout curing. Furthermore, introducing drainage under multiaxial stress conditions significantly mitigates elevated positive PWP by facilitating rapid dissipation of excess pore water. Drainage also effectively prevents the “resaturation effect” even under high horizontal closure stresses (rockwall closure 2), maintaining higher and more stable suction in CPB throughout curing. These findings underscore the critical influence of multiaxial stress conditions on pore water pressure in CPB, emphasizing the necessity of accounting for these coupled factors in order to manage pore pressure effectively, ensure barricade safety, and enhance the overall stability of CPB in deep mining operations.

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 score0.820
Threshold uncertainty score0.639

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 head0.205
Teacher spread0.198 · 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".

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Citations3
Published2025
Admission routes2
Has abstractyes

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