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Record W4285799966 · doi:10.1680/jphmg.21.00019

Pore-water pressure and liquefaction response of layered fine soils undergoing cementation

2022· article· en· W4285799966 on OpenAlexaff
Imad Alainachi, Mamadou Fall

Bibliographic record

VenueInternational Journal of Physical Modelling in Geotechnics · 2022
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsLiquefactionPore water pressureGeotechnical engineeringCementation (geology)Earthquake shaking tableWater tableSoil waterSettlement (finance)GeologySoil liquefactionGroundwaterMaterials scienceComposite materialSoil scienceCement

Abstract

fetched live from OpenAlex

Cemented paste backfill (CPB) is fine-grained soil undergoing cementation. It is widely used in mining operations for ground support and tailings disposal. In the field, CPB may be placed in one layer (continuous filing), or multiple layers (discontinuous or sequential filling). Until now, no studies have addressed the effect of the different filling strategies on the CPB response during cyclic events by using the shaking table technique. This paper presents new findings regarding the effect of the different filling strategies of CPB on its geotechnical response to dynamic loading. Samples were prepared with different scenarios, including one layered-CPB sample (discontinuous filling), in which each layer was cured for a different duration, and two unlayered-CPB samples (continuous filling), one of which was cured for 2.5 h and the other for 4.0 h. All samples were exposed to the same cyclic loading conditions using a one-dimensional shaking table. Geotechnical parameters, including pore-water pressure, settlement, volumetric water content and liquefaction susceptibility, were monitored or determined before, during and after shaking. The results indicate that layered-CPB samples are resistant to liquefaction under the studied loading conditions, while the unlayered-CPB samples are prone to liquefaction under the studied conditions when they are cured for less than 4.0 h.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.250

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 head0.014
GPT teacher head0.229
Teacher spread0.215 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Physical Modelling in GeotechnicsSame topicTailings Management and PropertiesFrench-language works237,207