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Record W2804917946 · doi:10.1139/cjce-2017-0671

Fatigue life evaluation of pavement embankments made with tire derived aggregates

2018· article· en· W2804917946 on OpenAlexaffvenueabout
Arian Asefzadeh, Leila Hashemian, Alireza Bayat

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFalling weight deflectometerScrapAsphaltEngineeringGeotechnical engineeringRoad constructionEnvironmental scienceCivil engineeringStructural engineeringSubgradeMaterials science

Abstract

fetched live from OpenAlex

Rapid growth of populations and extension of societies leads to the production of waste by-products, which puts a burden on landfills. To address this issue, tire derived aggregates (TDA) from scrap tires have been used as road embankments in several projects. Three different test sections using different TDA, and TDA and soil mixtures, were constructed at the Integrated Road Research Facility test road in Edmonton, Alberta, Canada. Based on falling weight deflectometer tests in different months, the fatigue life performance of the TDA embankments was evaluated against that of a conventional control section using the measured horizontal strains at the bottom of the asphalt layer and the Asphalt Institute’s fatigue model. The results showed satisfactory performance of all three TDA test sections and significantly longer fatigue lives as opposed to the fatigue life of the control section. This analysis showed compelling evidence regarding the long-term performance of TDA material as road embankments in construction projects.

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 score0.060
Threshold uncertainty score0.617

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 head0.019
GPT teacher head0.212
Teacher spread0.192 · 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

Citations5
Published2018
Admission routes3
Has abstractyes

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