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Record W2997322992 · doi:10.1111/ffe.13176

Fatigue behaviour of dry or partially saturated hot mix asphalt (HMA)

2019· article· en· W2997322992 on OpenAlexaff
Sébastien Lamothe, Daniel Perraton, Hervé Di Benedetto

Bibliographic record

VenueFatigue & Fracture of Engineering Materials & Structures · 2019
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsAsphaltMaterials scienceVoid (composites)Composite materialStiffnessAsphalt pavementGeotechnical engineeringGeology

Abstract

fetched live from OpenAlex

Abstract This paper analyses the water, the degree of saturation, and the void content effects on the fatigue behaviour of hot mix asphalt (HMA) samples mixed in the laboratory. Some results on stiffness are also given. Fatigue characterization was carried out through a uniaxial tension‐compression (T‐C) test performed in a controlled‐strain mode, at 10°C and 10 Hz, on cylindrical samples. Our results show that the stiffness is not significantly affected by the water. This finding could be attributed to the short period of immersion of samples in water, low testing temperature, low void content of tested samples, and high viscosity of bitumen used. Furthermore, the fatigue resistance of HMA partially saturated with water (PSW) is lower than the one obtained for dry materials.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.000

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 head0.018
GPT teacher head0.259
Teacher spread0.242 · 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 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

Citations13
Published2019
Admission routes1
Has abstractyes

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