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Record W2090649818 · doi:10.1139/t00-099

Static response of fly ash columnar improved ground

2001· article· en· W2090649818 on OpenAlexvenueno aff
Ali Porbaha, Trilochan Pradhan, Takeshi Kishida

Bibliographic record

VenueCanadian Geotechnical Journal · 2001
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
Fundersnot available
KeywordsGeotechnical engineeringConsolidation (business)Fly ashOverburden pressureMaterials sciencePore water pressureComposite numberTriaxial shear testSoil waterComposite materialShear (geology)GeologySoil science

Abstract

fetched live from OpenAlex

This study presents the results of a series of monotonic undrained triaxial compression tests on clay specimens improved by columnar reinforcement. The process of loading and stress redistribution of a fly ash – clay specimen (FCS), in comparison with a sand–clay specimen (SCS), is examined in terms of stress–strain characteristics, generation of excess pore-water pressure, effective and total earth pressures, development of stress concentration, and the normalized undrained shear strength of the improved soil. It was found, predictably, that the deviator stress of the composite specimens was influenced by the consolidation stress, replacement area ratio, and properties of the column material. The stress concentration at the top of the composite ground which depends on the loading stage reaches a peak after the consolidation state and is reduced due to stress redistribution between the column and the soft ground. In terms of improvement effects, the mean shear strengths of FCS and SCS relative to the clay specimen are three and seven times greater, respectively, for a replacement area ratio of 49%.Key words: composite ground, fly ash, soil improvement, soft ground, triaxial test.

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 score0.002
Threshold uncertainty score0.007

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)0.0020.000

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 head0.193
Teacher spread0.185 · 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".

Quick stats

Citations13
Published2001
Admission routes1
Has abstractyes

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