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Record W2154970932 · doi:10.1139/cjce-2013-0080

Warm mix asphalt by water-containing methodology: a laboratory study on workability properties versus micro-foaming time

2013· article· en· W2154970932 on OpenAlexaffvenue
Rosolino Vaiana, Teresa Iuele, Vincenzo Gallelli, Susan Tighe

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCompactionAsphaltMixing (physics)Materials scienceAsphalt pavementEnvironmental scienceGeotechnical engineeringComposite materialGeology

Abstract

fetched live from OpenAlex

This paper focuses on a laboratory investigation of compaction characteristics of warm mix asphalt produced with the addition of synthetic zeolites. The influence of the time elapsed between mixing and compaction operations on mix compactibility was evaluated to define an optimum “micro-foaming time” (MFT), in which the additive can completely release the water contained. A comparison between traditional hot mix asphalt and warm mixes was carried out; two compaction methods (impact and gyratory) were used. Mix compactibility was firstly evaluated in terms of air voids content for each condition of compaction (immediately after mixing or after 1–2 h of storage in an oven). Mix resistance to densification and to distortion was investigated by means of compaction indexes and traffic indexes. Data showed that the foaming process due to the addition of the zeolite has a peak value of intensity after 1 h of MFT. This effect seems to vanish after a longer period of time. Outcomes of this study are expected to benefit both practitioners and researchers.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score1.000

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 communication0.0000.001
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 head0.035
GPT teacher head0.232
Teacher spread0.197 · 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.

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

Citations22
Published2013
Admission routes2
Has abstractyes

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