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Record W2084020608 · doi:10.1139/l09-163

Chemical model to explain asphalt binder and asphalt–aggregate interface behaviors

2010· article· en· W2084020608 on OpenAlexvenueno aff
Dong-Woo Cho, Kyoungchul Kim, Min-Jae Lee

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2010
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsAsphaltHardening (computing)MoistureRheologyAggregate (composite)Materials scienceComposite materialGeotechnical engineeringEngineering

Abstract

fetched live from OpenAlex

The behavior of asphalt mixtures is very complicated due to structural configuration and interfacial friction of aggregates as well as chemical and rheological reactions of the asphalt binder itself or with the aggregates. Furthermore, this complex response is more complicated under various loads, temperatures, and other environmental factors. To control the complex responses and reduce the complex factors, a DSR moisture damage test using small rock disks was developed. This paper focuses on the more fundamental concepts to explain asphalt and asphalt–aggregate bond behavior exhibited under the newly-developed DSR moisture damage test. The traditional model of asphalt structure is based on the theory of colloid and surface chemistry. Although this traditional model can explain many physical phenomena of asphalt structure, it cannot explain all the asphalt behaviors, such as steric hardening. Therefore, more general, but fundamental concepts may be required to attain insight of the material. As one of the possible concepts, a self-assembly concept in supramolecular chemistry is proposed and phenomena and results of the DSR moisture damage test are explained by the concept.

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 score0.109
Threshold uncertainty score0.931

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 integrity0.0000.001
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 head0.012
GPT teacher head0.225
Teacher spread0.213 · 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

Citations11
Published2010
Admission routes1
Has abstractyes

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