MétaCan
Menu
Back to cohort
Record W4361265498 · doi:10.1139/cjce-2022-0319

Characterization of styrene-butadiene-styrene (SBS)-modified asphalt binders using the bending beam rheometer and the asphalt binder cracking device

2023· article· en· W4361265498 on OpenAlexaffvenue
Mike Aurilio, Pejoohan Tavassoti, Michael Elwardany, Hassan Baaj

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAsphaltMaterials scienceRheometerCrackingComposite materialRheologyCreepDynamic shear rheometerStyrene-butadieneBendingStyrenePolymer

Abstract

fetched live from OpenAlex

The addition of styrene butadiene styrene (SBS) to asphalt binders has led to enhanced performance in pavements across the entire range of working temperatures. SBS-modified binders have also proven to be more difficult to characterize in terms of their rheological properties. Low-temperature properties of asphalt binders are typically evaluated using the bending beam rheometer (BBR), which was developed to measure creep stiffness. Recent refinements to the BBR analysis have led to the development of Δ T c which is meant to provide more insight into the relaxation properties of the binder. The Asphalt Binder Cracking Device (ABCD) was developed to improve on this characterization by also taking into consideration the failure strength and coefficient of thermal contraction. Previous research has shown that the ABCD provides more valuable insight into the effect of SBS on the low-temperature properties of asphalt binders. This paper will evaluate the ability of these two low-temperature tests to characterize the performance of five different asphalt binders with increasing concentrations of SBS. It was found that the evaluation of the materials using Δ T c was inconsistent with binder type and generally indicated that SBS reduced cracking resistance, while the ABCD critical temperature and the proposed Δ T f parameter generally showed an improved correlation with SBS concentration.

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)0.002
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.232
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.

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

Citations5
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Civil EngineeringSame topicAsphalt Pavement Performance EvaluationFrench-language works237,207