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Record W2033097136 · doi:10.1139/l09-118

Effects of warm mix asphalt additives on performance properties of polymer modified asphalt binders

2010· article· en· W2033097136 on OpenAlexvenueno aff
Hakseo Kim, Soon-Jae Lee, Serji N. Amirkhanian

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2010
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsDynamic shear rheometerAsphaltMaterials scienceRutComposite materialRheometerRotational viscosityCrackingWaxRheologyViscosity

Abstract

fetched live from OpenAlex

This study presents an experimental evaluation for the performance properties of polymer modified asphalt (PMA) binders containing warm mix asphalt (WMA) additives. The PMA binders with the additives were produced using two of the available warm asphalt processes (i.e., Aspha-min and Sasobit) and three PMA binders graded as performance grade (PG) 76-22. The warm PMA binders were artificially short-term and then long-term aged using the rolling thin film oven (RTFO) and pressure aging vessel (PAV) procedures. Superpave binder tests were carried out on the binders through the rotational viscometer (RV), the dynamic shear rheometer (DSR), and the bending beam rheometer (BBR). In general, the results of this research indicated that (1) the addition of the WMA additives into the PMA binders showed positive effects on increasing rutting resistance at high temperature (based on the high failure temperature values from the DSR test); (2) the PMA binders containing the additives were observed to be less resistant to fatigue cracking at intermediate temperatures compared to the control PMA binders (based on the G*sin δ values at 25 °C from the DSR test); and (3) the addition of wax additive represented a possible lower resistance on low temperature cracking (based on the stiffness and the m-value at –12 °C from the BBR test).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.010
GPT teacher head0.183
Teacher spread0.173 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations57
Published2010
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Civil EngineeringSame topicAsphalt Pavement Performance EvaluationFrench-language works237,207