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Record W608553663

Thermo-mechanical Properties of Stone Mastic Asphalt (SMA) - Experimentation and Rheological Testing

2006· article· en· W608553663 on OpenAlexaboutno aff
Daniel Perraton, Hervé Di Benedetto, François Olard, Hassan Baaj, Cédric Sauzeat

Bibliographic record

Venue10TH INTERNATIONAL CONFERENCE ON ASPHALT PAVEMENTS - AUGUST 12 TO 17, 2006, QUEBEC CITY, CANADA · 2006
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsSMA*AsphaltMaterials scienceRheologyUltimate tensile strengthComposite materialTension (geology)ModulusRutStress (linguistics)Compression (physics)ThermalGeotechnical engineeringGeologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

Although a high content of unmodified binder is used, Stone Mastic Asphalt (SMA) generally shows good resistance to rutting due to the stone-to-stone contact. In Quebec, a test section was built in 2004 to evaluate the performance of SMA used as overlay for highly cracked pavements. Experimental results on the thermo-mechanical behaviour of SMA are presented herein (Complex modulus, Thermal coefficient, direct tension and compression tests and Thermal Stress Restrained Specimen Test-TSRST). The DBN model (Di Benedetto and Neifar) based on a thermo-visco-elasto-plastic approach was adopted for the modeling of experimental data. Numerical simulations show the need to consider non-linear behaviour for an accurate prediction of stress evolution in the TSRST. The DBN model is also used to evaluate the variation of the thermal stress under sinusoidal temperature variation with a 24-hour period. For the first 3 to 5 cycles, the maximum thermal tensile stress at higher cycles increases comparing to the previous cycles. Beyond that, the maximum tensile stress stabilizes. This phenomenon is important for Quebec environment during thaw periods where temperature variations are relatively high.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.296
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.066
GPT teacher head0.271
Teacher spread0.206 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

Explore more

Same venue10TH INTERNATIONAL CONFERENCE ON ASPHALT PAVEMENTS - AUGUST 12 TO 17, 2006, QUEBEC CITY, CANADASame topicAsphalt Pavement Performance EvaluationFrench-language works237,207