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Record W4410943255 · doi:10.1139/cgj-2024-0507

Effects of rubber-intermixed ballast on train loading response through field monitoring in Western Sydney

2025· article· en· W4410943255 on OpenAlexvenueno aff
Buddhima Indraratna, Chathuri Arachchige, Cholachat Rujikiatkamjorn, Trung Ngo, Yujie Qi, Ameyu Tucho

Bibliographic record

VenueCanadian Geotechnical Journal · 2025
Typearticle
Languageen
FieldEngineering
TopicRailway Engineering and Dynamics
Canadian institutionsnot available
FundersAustralian Research Council
KeywordsBallastGeotechnical engineeringNatural rubberField (mathematics)EngineeringGeologyForensic engineeringStructural engineeringEnvironmental scienceMaterials scienceComposite materialElectrical engineering

Abstract

fetched live from OpenAlex

The use of waste tyres in transportation infrastructure promotes environmentally sustainable engineering practices and reduces the cost of transportation and disposal. Laboratory testing has shown that a Rubber Intermixed Ballast System (RIBS) has significant advantages over conventional ballast. This study extends the evaluation of RIBS via a fully instrumented field trial near Western Sydney to assess its compatibility and efficiency under real-life conditions. The trial revealed a beneficial redistribution of stress along the depth of the track, despite an initial increase in deformation during construction and stabilizing the track in the initial loading phases. The measured acceleration response indicated a reduction of ground vibrations in the RIBS track, while the reduced particle breakage suggested its lifespan would exceed that of conventional ballast. Finite element modelling (FEM) of the RIBS track, calibrated with large-scale triaxial tests and field data, was carried out under moving wheel loads to compare its performance with a conventional ballasted track. The FEM simulations highlighted the differences in vertical stress and track settlement at varying train speeds. These findings indicate that RIBS support a circular economy and also offer a sustainable approach to stabilizing ballasted tracks by enhancing their longevity and reducing their maintenance costs.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.454
Threshold uncertainty score0.746

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 integrity0.0000.001
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 head0.006
GPT teacher head0.223
Teacher spread0.217 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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