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Record W2912973023 · doi:10.1139/cgj-2018-0630

Characterization of static and dynamic geotechnical properties and behaviors of fine coal refuse

2019· article· en· W2912973023 on OpenAlexvenueno aff
Sajjad Salam, Ming Xiao, Arash Khosravifar, Min Liew, Shimin Liu, Jamal Rostami

Bibliographic record

VenueCanadian Geotechnical Journal · 2019
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
FundersOffice of Surface Mining Reclamation and Enforcement
KeywordsGeotechnical engineeringLiquefactionShearing (physics)SlurryDirect shear testPore water pressureCoalOverburden pressureHydraulic conductivityMaterials scienceShear (geology)GeologyComposite materialSoil waterEngineeringWaste managementSoil science

Abstract

fetched live from OpenAlex

The geotechnical properties, cyclic behavior, and liquefaction resistance of in situ fine coal refuse (FCR) have not been sufficiently investigated. This paper presents the characterization of static and dynamic geotechnical properties of in situ coal slurry samples. Representative coal slurry samples were taken from two coal slurry impoundments in the Appalachian coalfields in the USA. Standard penetration tests (SPTs) were conducted. Index properties, hydraulic conductivity, shear strength, and shear stiffness of the FCR were determined. The geotechnical properties of the representative FCR were found significantly dependent on the location and depth of the samples. However, the FCR samples were classified as soft and low plasticity silty sands to sandy silts. Cyclic direct simple shear (DSS) tests were conducted on representative samples prepared using slurry deposition method to evaluate the liquefaction resistance and cyclic behavior of FCR. The cyclic stress ratio – number of cycles required for liquefaction occurrence (CSR–N) curve for FCR was established. The cyclic resistance of FCR compared well with the empirical correlations for sand-like materials, though the stress–strain behavior and pore-water pressure generation exhibited clay-like behavior. Each cyclic DSS test was followed by a static shearing to assess the post-liquefaction shear strength of the FCR. Significant decrease in shear modulus and dilative behavior were observed after liquefaction.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.770
Threshold uncertainty score0.608

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 head0.006
GPT teacher head0.180
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

Citations16
Published2019
Admission routes1
Has abstractyes

Explore more

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