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Record W3135231597 · doi:10.9798/kosham.2021.21.1.199

Temperature Distribution of Railway Tunnels in Winter

2021· article· en· W3135231597 on OpenAlexaff
Y.S. Park, Se‐Hee Lee, KookHwan Cho

Bibliographic record

VenueKorean Society of Hazard Mitigation · 2021
Typearticle
Languageen
FieldEngineering
TopicRailway Engineering and Dynamics
Canadian institutionsOptech (Canada)
FundersKorea Railroad Research Institute
KeywordsTrainSlabRange (aeronautics)Atmospheric temperature rangeEnvironmental scienceGeotechnical engineeringMeteorologyMaterials scienceGeologyEngineeringStructural engineeringComposite materialPhysicsGeography

Abstract

fetched live from OpenAlex

The freezing water around the tunnel lining, which is caused by the external temperature during winter, damages portions of tunnel structures, such as the lining and concrete slab track. To investigate the influence of freezing temperature, a total of 50 temperature gauges were installed from the tunnel entrance to 3,270 m. The total length of the tunnel was 8,293 m. The variation in temperature along the tunnel was measured during winter. The correlation between the variation in temperature and the influence of train operation at a speed of 130-150 km/h was analyzed. The duration of the increasing freezing temperature range influenced by train operation was also analyzed and displayed in the results. The results demonstrated that the variation in temperature according to the train operation could be recovered in 30 min. Therefore, when considering the freezing range of a tunnel where trains are travelling at intervals of approximately 30 min, it was judged that the influence factor will be negligible owing to the train operation.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.454

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 head0.005
GPT teacher head0.195
Teacher spread0.190 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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