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Record W2135942198 · doi:10.1080/10298436.2011.573557

Rheological analysis of multi-stress creep recovery (MSCR) test

2011· article· en· W2135942198 on OpenAlexafffund
Thamindra Lakshan Jayanthi Wasage, Jiri Stastna, Ludo Zanzotto

Bibliographic record

VenueInternational Journal of Pavement Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaFederal Highway Administration
KeywordsRutAsphaltCreepViscoelasticityRheologyAsphalt pavementMaterials scienceGeotechnical engineeringEngineeringStructural engineeringForensic engineeringComposite material

Abstract

fetched live from OpenAlex

It has been known for some time that the current AASHTO M 320-05 specification does not address the true rutting potential of modified asphalt binders. The multi-stress creep recovery (MSCR) test was proposed by the United States Federal Highway Administration to replace the AASHTO M 320-05 high-temperature specification parameter and various SHRP+test methods. The new parameter of non-recoverable compliance, Jnr, is currently being considered as a replacement for the Superpave high-temperature binder parameter of |G*|/sin δ (ω = 10 rad/s) (AASHTO TP 70-09). An investigation of the suggested new parameter in capturing the rutting potential and a rheological analysis of the MSCR test method were carried out for conventional and modified asphalt binders and are reported in this paper. The laboratory wheel tracking test was conducted to study the rutting potential of asphalt mixes prepared with the same asphalt binders. Correlation of the new parameter, Jnr, with rutting in asphalt mixes is briefly discussed. A linear viscoelastic compliance model was developed to describe the MSCR test and is also discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.036
GPT teacher head0.259
Teacher spread0.223 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations187
Published2011
Admission routes2
Has abstractyes

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