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Record W4385619557 · doi:10.5267/j.esm.2023.7.003

A study of the shear strength properties of expansive soil treated with fly ash admixture

2023· article· en· W4385619557 on OpenAlexvenueno aff
Jajati Keshari Naik, Dilip Kumar Bagal, Pradyut Kumar Muduli

Bibliographic record

VenueEngineering Solid Mechanics · 2023
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
Fundersnot available
KeywordsFly ashExpansive clayGeotechnical engineeringShear strength (soil)Materials scienceShear (geology)ExpansiveDirect shear testDebrisSoil waterEnvironmental scienceGeologyComposite materialCompressive strengthSoil science

Abstract

fetched live from OpenAlex

The behavior of clay minerals in expansive soils causes them to exhibit shrink-swell characteristics, making them unsuitable for engineering purposes in their natural state. To address this problem, researchers conducted direct shear experiments using fly ash as an admixture and black cotton soil as an expanding soil to explore the strength parameter. The experiments were conducted with varying amounts of fly ash ranging from 2% to 20%. Two arrangements of test series were made, and in the principal series, tests were made utilizing five unique densities and comparing dampness contents. The outcomes showed that the point of inside grating and union expanded directly up to the ideal dampness content and most significant dry thickness before diminishing. The subsequent series showed that the end of inward rubbing grew straightly with the expansion of fly debris admixture, yet attachment reduced after 10% admixture. The decrease in shear strength was because of the diminished passion, as the fly debris' cohesionless attributes took over as the admixture rate increased above 10%. Based on these findings, adding fly ash in small quantities to black cotton soil is recommended to avoid weakening it.

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 score0.076
Threshold uncertainty score0.660

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.183
Teacher spread0.174 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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