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Record W4409765412 · doi:10.1061/jmcee7.mteng-19725

Sustainable Recycling of Reclaimed Asphalt in Atypical Low-Asphaltene Binders Made from Athabasca Oil Sands Bitumen

2025· article· en· W4409765412 on OpenAlexaffabout
Hanwalle M.C. Nawarathna, Simon A.M. Hesp

Bibliographic record

VenueJournal of Materials in Civil Engineering · 2025
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsQueen's University
Fundersnot available
KeywordsAsphaltOil sandsAsphalteneRutEnvironmental scienceWaste managementAsphalt pavementGeotechnical engineeringGeologyMaterials scienceEngineeringComposite material

Abstract

fetched live from OpenAlex

Utilization of reclaimed asphalt pavement (RAP) and reclaimed asphalt shingles (RAS) in road construction optimizes the use of natural resources by saving on virgin binder and aggregate and, therefore, reducing the overall environmental impact of the industry. This paper presents experimental results of using RAP and RAS with virgin asphalt binders from oil sands deposits in Alberta, Canada. Atypical virgin binder A from an Athabasca source and standard virgin binder C from a Cold Lake source were modified at two different levels of RAP (20% and 40% by weight) and with RAS from a single source. Each blend was tested under three different aging conditions [unaged, rolling thin film oven (RTFO)-aged and pressure aging vessel (PAV)-aged for 20 h]. The RAP sources used in this study came from rehabilitation contracts on Highway 7 and Highway 403 in Ontario, while the RAS was obtained from tear-off shingles sourced locally. Rheological results showed that atypical virgin binder A, containing lower amounts of asphaltenes, accommodates more RAP than harder binder C. The results reveal that A+20% RAP can be used as a lower cost alternative for virgin C, as the two materials possess nearly the same rheological grade (PG 58-28) and flow characteristics. Given the abundance of atypical Athabasca oil sands crudes, it is worthwhile to further investigate low-asphaltene binders produced from such sources for the improved recycling of reclaimed asphalt.

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)0.001
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.778

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.006
GPT teacher head0.225
Teacher spread0.219 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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