MétaCan
Menu
Back to cohort
Record W4296743365 · doi:10.3390/su141811775

Evaluation of the Incorporation of Tire-Derived Aggregates (TDA) in Rigid Pavement Mix Designs

2022· article· en· W4296743365 on OpenAlexaff
Ahmad M. Abu Abdo, Hany El Naggar

Bibliographic record

VenueSustainability · 2022
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsDalhousie University
Fundersnot available
KeywordsSlabCrackingPortland cementNatural rubberMaterials scienceDeflection (physics)Fatigue crackingWaste managementCementEnvironmental scienceComposite materialStructural engineeringEngineering

Abstract

fetched live from OpenAlex

Owing to the extensive worldwide generation of solid wastes, such as rubber tires, and the resulting adverse environmental impacts, the incorporation of these waste materials in construction projects has become a widespread aim. However, concerns have arisen regarding the effects of rubber waste on the mechanical properties of Portland cement concrete (PCC) mixes. Thus, this study investigates the effects of replacing natural coarse aggregates with tire-derived aggregates (TDA). In PCC mixes, natural aggregates were replaced by 0, 10, 20, 40, 60, 80, and 100% TDA by volume, and the properties of these specimens were tested in the laboratory. The results obtained were then used as inputs for the KENPAVE software, to evaluate induced stresses, deflections, and cracking indices in rigid pavement slabs, with eleven different thicknesses, ranging from 200 to 300 mm in 10 mm increments. Stresses under different loading conditions decreased as PCC slab thickness and TDA content increased. Increased deflection and cracking indices resulting from adding TDA could be counteracted by increasing the PCC slab thickness by 10 mm. Moreover, environmental impacts and cost analyses were examined via PaLATE 2.0, which showed that the use of TDA could reduce energy consumption, harmful emissions, and material costs. Overall, this study indicates that the use of TDA in PCC mixes has benefits that can make it a good candidate for sustainable, ecofriendly rigid pavement construction projects.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.455
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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 head0.029
GPT teacher head0.268
Teacher spread0.238 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueSustainabilitySame topicInnovative concrete reinforcement materialsFrench-language works237,207