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Ground track response behaviour induced by train speed using seismic wave method

2022· article· en· W4293223114 on OpenAlexaff
Nurasma Yahaya, A. Ibrahim, J. Ahmad, A Ahmad, Mohd Ikmal Fazlan Rozli, Z Ramli

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicRailway Engineering and Dynamics
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsTrack (disk drive)AccelerationSettlement (finance)VibrationStiffnessCritical speedStructural engineeringGround vibrationsEngineeringGeodesyAcousticsGeologyComputer sciencePhysicsMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Ground track response analysis is an alternative method utilized to investigate the influence of ground-borne vibrations induced by speed train on track. This study intended to get an understanding about the responsive of ground towards vibration induced from moving train. To facilitate this study, non-destructive seismic wave method was performed using new application, Sirius M instrument to identify the peak vertical acceleration generated at various running speed and track locations. The result shows the vertical acceleration data signalized from transition wave generate through passing Electric Train Service (ETS) with maximum 140km.hr −1 speed train is higher than commuter with 120km.hr −1 speed train which are 1.935m.s −2 and 1.051m.s −2 respectively. Analysis of vertical acceleration data based on different track locations corresponding to the ETS speed resulting higher peak acceleration at stable track, KM21 compared to settlement susceptible track, KM20.75 which are 6.565m.s −2 and 1.935m.s −2 respectively. The values obtained from this study indicated ground-borne vibration influenced by speed of train and different type of embankment foundation. This data can be used to assess the influences of train type and speed. Moreover, this on-site ground response measurement is potentially useful as an alternative method to determine the soil stiffness which provide an indication to the possible problematic ground susceptible to the settlement.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.485
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.028
GPT teacher head0.244
Teacher spread0.216 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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