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Record W4402956463 · doi:10.18280/mmep.110904

Influence of Rail-End Bolt Hole Position and Clearance on Stress and Displacement of Rail Using Finite Element Analysis

2024· article· en· W4402956463 on OpenAlexvenueno aff
Sai Kham Le, Jittraporn Wongsa‐Ngam

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2024
Typearticle
Languageen
FieldEngineering
TopicRailway Engineering and Dynamics
Canadian institutionsnot available
FundersKing Mongkut's Institute of Technology Ladkrabang
KeywordsFinite element methodDisplacement (psychology)Structural engineeringStress (linguistics)Position (finance)EngineeringMaterials scienceMechanicsPhysicsBusiness

Abstract

fetched live from OpenAlex

In a bolted rail joint, the two rail ends are connected with fishplates on both sides and adjusted with fishbolts.Such joints help to facilitate the smooth running of the train wheels over the joints.However, the lifetime of a bolted rail joint is shorter than the lifetime of a continuous rail because of the complex interactions that occur at the contact surfaces of the joint components and at the rail ends.In this paper, the bolted rail joint structure components are first modeled in ABAQUS/CAE.The effects of rail-end bolt hole position and bolt-hole clearance were considered in the rail.Then, finite element analysis (FEA) of the bolted rail joint assembly was performed to determine the stress, particularly on the upper fillet and bolt holes of the rail, as well as the vertical displacement of the rail end, when static loading was applied at the rail end.The numerical simulation results showed that the rail-end bolt hole positions affect to von-Mises stress and vertical displacement, whereas bolt-hole clearance has a relative minor effect on stress and vertical displacement.To avoid stress concentration that may cause further failure, the position of the rail-end bolt holes should be carefully considered.

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 score0.480
Threshold uncertainty score0.763

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 head0.010
GPT teacher head0.208
Teacher spread0.198 · 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
Published2024
Admission routes1
Has abstractyes

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