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Effects of Tire Pyrolysis Oil (TPO) on the Rheological Properties of Bitumen

2021· article· en· W3165044191 on OpenAlexaff
Abdulnaser M. Al-Sabaeei, Madzlan Napiah, Muslich Hartadi Sutanto, Wesam Salah Alaloul, Nura Bala

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAsphaltDynamic shear rheometerRheologySoftening pointMaterials scienceRutComposite materialDynamic modulusViscoelasticityDynamic mechanical analysisPolymer

Abstract

fetched live from OpenAlex

Abstract Millions of tires are produced worldwide every year and after a short time become waste. This is considering a massive waste need to be incorporated in various sustainable applications such as in a bitumen modification. In this study, tire pyrolysis oil-modified bitumen was prepared at 0%, 5%, 10%, and 15% by total weight of the blend. The influence of tire pyrolysis oil (TPO) on the conventional and high-temperature rheological properties of bitumen was evaluated by conducting penetration grade, ring and ball, dynamic viscosity, complex modulus, phase angle, and rutting resistance evaluations. Results show that the addition of TPO into base bitumen reduces the penetration values and slight reduction in softening points of modified bitumen which indicating the consistency and applicability of the TPO as a bitumen modifier. Based on the dynamic viscosity and temperature sweep test performed by a dynamic shear rheometer, it was observed that overall, TPO improved the viscosity, complex modulus, phase angle, and permanent deformation of bitumen at the temperature range of 40 to 76 °C, particularly at lower TPO content. Furthermore, TPO-modified bitumen exhibits rutting resistance better than base bitumen which could be attributed to the improvement in the elastic behaviour of bitumen with the addition of TPO. 15%TPO-modified bitumen show adequate rheological properties to be used as an alternative for base bitumen in hot regions pavement applications.

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 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 score0.008
Threshold uncertainty score0.359

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)0.0000.000

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 head0.018
GPT teacher head0.199
Teacher spread0.181 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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