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Record W1857376878 · doi:10.1139/t08-072

Cyclic strength of a natural liquefiable sand stabilized with colloidal silica grout

2008· article· en· W1857376878 on OpenAlexvenueno aff
J. A. Dìaz‐Rodrìguez, V. M. Antonio-Izarraras, Paola Bandini, J. A. López-Molina

Bibliographic record

VenueCanadian Geotechnical Journal · 2008
Typearticle
Languageen
FieldEngineering
TopicGrouting, Rheology, and Soil Mechanics
Canadian institutionsnot available
FundersUniversidad Nacional Autónoma de México
KeywordsGroutColloidal silicaLiquefactionGeotechnical engineeringSiltPore water pressureMaterials scienceColloidCompactionGeologyComposite materialEngineeringChemical engineering

Abstract

fetched live from OpenAlex

This paper summarizes the experimental results of a series of cyclic simple shear tests on liquefiable silty sand with and without sample improvement with colloidal silica grout. The objective of the paper is to evaluate the effectiveness of colloidal silica grouting in reducing the liquefaction potential of natural silty sand. Colloidal silica was selected as a stabilizing material due to its low viscosity, wide range of gel times, nontoxicity, and low cost. The soil tested in this experimental program is a poorly graded sand with 11.5% of nonplastic silt from the Port of Lázaro Cárdenas, México. Colloidal silica treated and untreated sand specimens show different pore pressure response and deformation behavior under cyclic loading in simple shear tests. The results indicate that, for a given initial relative density and initial effective vertical stress, liquefiable silty sand specimens stabilized with colloidal silica grout generally exhibit significant gain in liquefaction resistance compared with untreated specimens. It was also found that the colloidal silica grout reduces considerably the rates of pore pressure generation and shear strain of the silty sand specimens subjected to cyclic loading.

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 score0.212
Threshold uncertainty score0.774

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 head0.007
GPT teacher head0.182
Teacher spread0.175 · 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

Citations88
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicGrouting, Rheology, and Soil MechanicsFrench-language works237,207