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Record W2044352197 · doi:10.3141/1810-01

Impact of Different Types of Modification on Low-Temperature Tensile Strength and T <sub>critical</sub> of Asphalt Binders

2002· article· en· W2044352197 on OpenAlexafffund
S Ho, Ludo Zanzotto, D MacLeod

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2002
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsHusky Energy (Canada)University of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAsphaltMaterials scienceComposite materialLimeRheometerUltimate tensile strengthPolymerMetallurgyRheology

Abstract

fetched live from OpenAlex

The introduction of the Superpave®asphalt binder specification provided the asphalt industry with a useful guideline for choosing appropriate materials to meet the requirements of a specific climate. Acid, alkaline, and polymer modification are just some of the ways to modify asphalt to meet the Superpave specification. The direct tension test (DTT) technique was applied to study the low-temperature properties of modified asphalt in terms of DTT failure stress values and the critical cracking temperature ( T critical ). The bending beam rheometer (BBR) usually failed to detect improvement in low-temperature performance in polymer-modified asphalt (PMA). DTT results show that elastomeric polymer modification improves the low-temperature performance of PMA. In some PMAs, the failure stress value was higher than 9.5 MPa. The DTT technique for PMA was also reviewed. The effect of acid and alkaline modifiers on asphalt materials was studied. Acid or alkaline modification of asphalt was found to be only temporary and to be reversible. Acid modification of asphalt can be reversed by reaction with alkaline materials such as lime or antistripping agents. Alkaline modification of asphalt can be reversed by reaction with acidic materials such as carbon dioxide. Alkaline also can be washed away by water. Even though the BBR suggested a slight improvement in the low-temperature performance in acid- or alkalinemodified asphalt, the DTT failure stress values and T critical did not confirm this improvement. A relatively simple procedure that allows detection of acid or alkaline modification of asphalt materials is described.

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)0.002
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 score0.617
Threshold uncertainty score0.646

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.071
GPT teacher head0.363
Teacher spread0.291 · 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

Citations30
Published2002
Admission routes2
Has abstractyes

Explore more

Same venueTransportation Research Record Journal of the Transportation Research BoardSame topicAsphalt Pavement Performance EvaluationFrench-language works237,207