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Record W1981192901 · doi:10.1139/t05-021

Performance of cement-stabilized retaining walls

2005· article· en· W1981192901 on OpenAlexvenueno aff
Mostafa A. Ismail

Bibliographic record

VenueCanadian Geotechnical Journal · 2005
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
Fundersnot available
KeywordsCentrifugeGeotechnical engineeringRetaining wallCementation (geology)Finite element methodCohesion (chemistry)CementBearing capacityPortland cementStructural engineeringEngineeringMaterials scienceGeologyComposite material

Abstract

fetched live from OpenAlex

This paper investigates the performance of a cement-stabilized retaining wall as a potentially economic solution for supporting vertical cuts in roads and embankments. This investigation was carried out through a comprehensive numerical and experimental program in which the stabilized wall was treated as a c′–ϕ soil. To optimize the design of the stabilized wall, a plane-strain finite element analysis was carried out, using the PLAXIS code, in a parametric study that varied the wall geometry and the shear strength parameters for both the wall and its surrounding soil. The performance of the stabilized retaining wall was verified by a centrifuge model test carried out at an equivalent acceleration of 67g for a sand treated with 3% Portland cement. The results have shown that the load-carrying capacity of the wall is affected primarily by both the cementation of the wall and the friction angle of the surrounding soil. There exists a threshold of cementation beyond which the stability does not increase when the failure mechanism is located completely inside the in situ soil. This critical cementation appears to be a crucial factor in maintaining an economic design for this type of wall. Centrifuge test results confirmed the satisfactory behaviour of cement-stabilized retaining walls.Key words: cement stabilization, retaining wall, cohesion, finite element, centrifuge testing.

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 score0.070
Threshold uncertainty score0.600

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 integrity0.0000.001
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 head0.008
GPT teacher head0.188
Teacher spread0.180 · 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

Citations13
Published2005
Admission routes1
Has abstractyes

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