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Record W4377098613 · doi:10.1177/03611981231170620

Laboratory Investigation into the Partial Replacement of Aggregates with Recycled High-Density Polyethylene in a Dense Graded Asphalt Mix

2023· article· en· W4377098613 on OpenAlexaff
S. Banfield, Xiomara Sánchez

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2023
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsHigh-density polyethyleneRutMaterials scienceAsphaltComposite materialPolyethyleneCrackingUltimate tensile strength

Abstract

fetched live from OpenAlex

Plastic waste is a growing concern today, as landfills fill up and pollution leads to global climatic problems. Some research has been conducted on using plastics in asphalt, but the effect that high-density polyethylene (HDPE) can have in the performance of the asphalt is not understood. This research examines the impact on the moisture damage, rutting, and cracking resistance of recycled HDPE plastics as a portion of aggregates in a dense graded asphalt mix. Two types of recycled HDPE were used—flakes and pellets. Mixes with 5% by volume of recycled HDPE were designed and compared with a control mix. The results indicate that the use of recycled HDPE allowed for a reduction of 0.5% binder requirement. Tensile strength ratio testing showed that, with no anti-stripping agent, the HDPE-modified mixes had acceptable moisture resistance. Both types of HDPE-modified mixes showcased superior rutting resistance based on the flow number parameter. However, the use of HDPE decreased the cracking resistance of the mixes measured with the Illinois Flexibility Index Test at intermediate temperatures. The dynamic modulus test indicated a decrease in the stiffness of the mixes at low temperatures and confirmed the increase of the stiffness at high operating temperatures. Overall, the results indicate that the use of HDPE as partial replacement of aggregates is feasible and future research could explore balancing the performance of the HDPE-modified mix.

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)0.008
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.054
GPT teacher head0.335
Teacher spread0.281 · 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 designObservational
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

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueTransportation Research Record Journal of the Transportation Research BoardSame topicAsphalt Pavement Performance EvaluationFrench-language works237,207