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Record W3209607667 · doi:10.1139/cgj-2021-0239

Hydraulic conductivity variation in compacted bentonite–fly ash mixes under constant-volume and free-swelling flow conditions

2021· article· en· W3209607667 on OpenAlexvenueno aff
Chandra Bhanu Gupt, Sanandam Bordoloi, Metta Niranjan Bhatlu, S. Sreedeep

Bibliographic record

VenueCanadian Geotechnical Journal · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBentoniteHydraulic conductivityFly ashGeotechnical engineeringSwellingMaterials scienceVolume (thermodynamics)Calcium silicate hydrateMineralogyPorosityComposite materialGeologySoil scienceThermodynamicsSoil waterCement

Abstract

fetched live from OpenAlex

Compacted bentonite–sand (B–S) and bentonite–fly ash (B–FA) are established combinations for the construction of landfill liners. This study determined the upper and lower bounds of equilibrium hydraulic conductivity (k eq ) of amended B under extended duration of flow. The k eq for constant-volume flow condition differed from free-swelling condition by more than two orders of magnitude due to the difference in geomaterial interaction, microstructural changes, and mineralization. Considering constant-volume and free-swelling condition, B–FA mix with class F and class C fulfilled the hydraulic conductivity criterion up to 70% and 30% amendment, respectively. The higher k eq observed for the B mixed with class C FA was attributed to the formation of porous calcium aluminium silicate hydrate gel and ettringite needle type minerals. The time taken to achieve equilibrium was inversely related to k eq by a power relationship. The data from this study were used to propose empirical relationships for estimating k eq (long-term) based on k obtained at 48 hours (short-term), plasticity and geomaterial type. The study reveals that FA can be used as an alternate for S as amendment material, and k eq based on free-swelling condition should be used for designing the liner.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.539
Threshold uncertainty score0.998

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)0.0030.000

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 head0.222
Teacher spread0.208 · 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.

Study designObservational
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

Citations10
Published2021
Admission routes1
Has abstractyes

Explore more

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