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Record W4388143645 · doi:10.17576/jkukm-2023-35(3)-22

Using Cement as Filler to Enhance Asphalt Mixes Performance in Hot Climate Regions

2023· article· en· W4388143645 on OpenAlexaff
Aioub H. Guha, Gabriel J. Assaf

Bibliographic record

VenueJurnal Kejuruteraan · 2023
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsRutAsphaltCementEnvironmental sciencePortland cementGeotechnical engineeringFiller (materials)Asphalt concreteMaterials scienceCivil engineeringEngineeringComposite material

Abstract

fetched live from OpenAlex

This paper investigates the addition of different percentages of ordinary Portland cement as a filler in conventional asphalt concrete for a range of heavy traffic. Road pavement agencies in hot areas face the daunting challenge of preserving their pavements in a fair to good condition to increase their lifespan. This challenge is due to the high occurrence of permanent pavement deformation via rutting, which is one of the major distress factors influencing pavements. This is a particularly serious issue in hot and arid countries which are closely associated with various aggravating factors. These aggravating factors include the choice of bitumen binder viscosity, the type of bitumen, the available low-quality materials, and the high environmental temperatures. Ultimately, poor performance will show within the first few years of service as permanent deformations such as rutting, shoving, and depressions. The examined properties include the resilient modulus and the resistance to rutting. Findings indicate that the resistance to rutting and the rigidity of the asphalt concrete are both substantially increased as the cement content is increased. Moreover, to meet the heavy traffic spectrum requirements, increasing the embedded cement content in the asphalt concrete improves pavement structural capacity. Finally, based on the rigidity expected for different cement levels, design curves are provided for pavement design in hot climates using low quality aggregate materials.

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 categoriesInsufficient payload (model declined to judge)
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 score0.146
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.042
GPT teacher head0.327
Teacher spread0.285 · 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.

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

Citations3
Published2023
Admission routes1
Has abstractyes

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