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Record W2086836040 · doi:10.3141/2154-14

Investigation of Hot-Mix Asphalt Dynamic Modulus by Means of Field-Measured Pavement Response

2010· article· en· W2086836040 on OpenAlexafffund
Alireza Bayat, Mark A. Knight

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2010
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsUniversity of WaterlooUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaMinistère des Transports
KeywordsDynamic modulusAsphaltAsphalt pavementModulusRutMaterials scienceComposite materialAsphalt concreteGeotechnical engineeringStructural engineeringDynamic mechanical analysisEngineeringPolymer

Abstract

fetched live from OpenAlex

The current Mechanistic–Empirical Pavement Design Guide (MEPDG) proposes the use of the laboratory dynamic modulus test to determine time–temperature-dependent properties of hot-mix asphalt (HMA) materials. To date, limited measurements have been performed to compare the HMA behavior of laboratory dynamic modulus test with the field measured pavement response. The objectives of this study were to compare and validate laboratory-determined HMA dynamic modulus with field-measured asphalt longitudinal strains. Under constant loading frequency, the laboratory-determined dynamic modulus for Hot Laid 3 (HL3) was found to decrease exponentially when the temperature of the asphalt mix increased. Controlled wheel load experiments, performed at a constant truck speed, found that HL3 asphalt longitudinal strain increased exponentially with an increase in asphalt middepth temperature. The comparison of both exponential relationships showed that the laboratory-determined dynamic modulus was inversely proportional to the field-measured asphalt longitudinal strain.

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)0.009
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.574
Threshold uncertainty score0.885

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.053
GPT teacher head0.344
Teacher spread0.292 · 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 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
Published2010
Admission routes2
Has abstractyes

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