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Record W3082874073 · doi:10.1139/cgj-2019-0722

One-dimensional (1D) immediate compression and creep in large particle-sized tire-derived aggregate (TDA) for leachate collection and removal systems (LCRSs)

2020· article· en· W3082874073 on OpenAlexaffvenue
Doyin Adesokan, Ian Fleming, Adam Hammerlindl

Bibliographic record

VenueCanadian Geotechnical Journal · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCreepVoid (composites)Void ratioMaterials scienceCompressive strengthGeotechnical engineeringCompression (physics)LeachateGeosyntheticsComposite materialAggregate (composite)Volume (thermodynamics)Waste managementGeologyEngineering

Abstract

fetched live from OpenAlex

Potential cost savings and environmental benefits are two reasons for using tire-derived aggregate (TDA) in place of gravel, or drainage geosynthetics, as drainage material in the leachate collection and removal systems (LCRSs) of waste disposal facilities. As a polymeric material, TDA is expected to undergo both immediate and time dependent compression (creep) under sustained compressive loading, and these may influence performance. The response of large particle-sized TDA — TDA with individual particle sizes generally greater than 50 mm — to large compressive loads up to 300 kPa was studied to assess void volume reduction from the individual and combined effects of immediate compression and creep. The results showed void volume reduction from creep, but this was considerably less than that from the immediate compression. The final void ratio appeared to be dependent on the initial void ratio (e 0 ), as well as on the applied load, but it did not appear to be dependent on the loading rate or to be influenced by elevated temperatures (up to 58 °C). Presented here are the details of the study, findings, and implications for practice.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.627
Threshold uncertainty score0.667

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 head0.021
GPT teacher head0.225
Teacher spread0.205 · 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 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

Citations5
Published2020
Admission routes2
Has abstractyes

Explore more

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