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Record W2219524445 · doi:10.1139/cgj-2014-0069

Small to intermediate strain properties of fly ashes with various carbon and biomass contents

2015· article· en· W2219524445 on OpenAlexvenueno aff
Hyunwook Choo, N. N. Nortey Yeboah, Susan E. Burns

Bibliographic record

VenueCanadian Geotechnical Journal · 2015
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
FundersSouthern Company
KeywordsFly ashVoid ratioOedometer testMaterials scienceStiffnessCarbon fibersCoalBiomass (ecology)Geotechnical engineeringComposite materialWaste managementEnvironmental scienceGeologySoil scienceSoil waterEngineering

Abstract

fetched live from OpenAlex

High-carbon-content fly ashes with biomass particles are typically landfilled in accordance with the ASTM C618 regulation. To quantify their geotechnical properties relating to storage and disposal, this study evaluates the small to intermediate strain properties of fly ashes with various carbon and biomass contents. Tested fly ashes had carbon contents ranging from 1.1% to 9.6%, resulting from co-combusting coal with biomass (biomass contents ranging from 0% to 8.2% by weight). The small-strain stiffness and intermediate-strain constrained modulus were evaluated using consolidation tests performed in a modified oedometer cell equipped with bender elements. It was found that initial void ratio governed the compressibility (or constrained modulus) of fly ashes, and with an increase in carbon and biomass contents, the small-strain stiffness of fly ashes decreased due to the decrease in number of direct contacts between microspheres. In addition, the interfine void ratio, e f , was employed instead of global void ratio to capture the alteration of interparticle contact or interparticle coordination between microspheres, due to the change in carbon and biomass contents. Finally, the stiffness in an overconsolidated state and the stiffness anisotropy of fly ashes were evaluated.

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 score0.032
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.179
Teacher spread0.156 · 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

Citations13
Published2015
Admission routes1
Has abstractyes

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