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Record W4403926412 · doi:10.1139/cjce-2024-0334

Study on performance deterioration of asphalt and asphalt mixtures containing Mafilon under internal salt freeze–thaw cycles

2024· article· en· W4403926412 on OpenAlexvenueno aff
Haihu Zhang, Jinsong Qian, Runhua Guo, Long Wen

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsAsphaltGeotechnical engineeringMaterials scienceComposite materialSalt (chemistry)Environmental scienceForensic engineeringEngineeringChemistry

Abstract

fetched live from OpenAlex

The purpose of this work is to determine the implications of internal salt freeze–thaw cycles (F–TCs) on performance deterioration to asphalt and asphalt mixtures containing Mafilon (MFL). The deterioration to different numbers of F–TCs and different MFL contents on asphalt properties and mechanism were investigated by physical properties tests and microcosmic tests. Then the damages of road performance indexes of asphalt mixtures containing different MFL contents were studied by road performance tests. The experimental results show that asphalt containing MFL after F–TCs has a remarkable decline in ductility and penetration, while growth in softening point. Internal salt F–TCs are most damaging to the cryogenic properties of asphalt. Chemical reactions and salt aging effects occur in salt F–TCs, raising the glass transition temperature of asphalt. Road performance tests indicate the deterioration of internal salt F–TCs to high temperature stability and water stability is the most pronounced, with 29.18% and 21.78% reduction, respectively.

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)0.000
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 score0.332
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.017
GPT teacher head0.237
Teacher spread0.220 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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