MétaCan
Menu
Back to cohort
Record W4416863039 · doi:10.1139/cjce-2025-0324

Pavement surface and base layer simultaneous reclamation with cement-emulsified asphalt: mix design, effectiveness, and mechanisms

2025· article· en· W4416863039 on OpenAlexvenueno aff
Yunwei Meng, Jiajun Shen, Xuzhi Liang

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsAsphaltCementVoid (composites)Ultimate tensile strengthScanning electron microscopeDynamic modulusRheometryAsphalt concreteModulusShear (geology)

Abstract

fetched live from OpenAlex

To address the limited co-recycling of asphalt surface and base layers and the lack of interfacial mechanism studies, this research proposes a composite cold recycling technology using cement-emulsified asphalt (CA) mortar. The method enables synchronous regeneration of reclaimed asphalt pavement (RAP) and reclaimed base material (RBP), with improved mechanical performance through optimized material proportions. A multiscale experimental design refined the RAP/RBP ratio, cement content, and emulsified asphalt dosage. Mechanical tests, pull-off strength, Dynamic Shear Rheometry (DSR), and scanning electron microscopy-energy dispersive X-ray spectroscopy (SEM-EDS) were conducted to evaluate performance and interfacial bonding. The optimal formulation (1.5% cement, 5% emulsified asphalt) achieved 0.85 MPa tensile strength and 9.8% void ratio. A 7–10 µm interfacial fusion depth and a 12.5% increase in dynamic shear modulus confirmed strong adhesion and fatigue resistance at the RAP interface. In contrast, the RBP interface exhibited irregular cement morphology and weaker bonding, indicating a need for further enhancement.

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: none
Teacher disagreement score0.701
Threshold uncertainty score0.722

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.011
GPT teacher head0.207
Teacher spread0.195 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

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