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Record W4396517043 · doi:10.1139/cgj-2023-0357

Centrifuge modeling of end-bearing slender energy pile performance under temperature cycles

2024· article· en· W4396517043 on OpenAlexvenueno aff
Long Chen, Yifan Hu, Zi Ye, Yang Zhou, Gangqiang Kong, Yonghui Chen

Bibliographic record

VenueCanadian Geotechnical Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsCentrifugePileGeotechnical engineeringBearing (navigation)GeologyBearing capacityEngineeringStructural engineeringComputer sciencePhysics

Abstract

fetched live from OpenAlex

Slender energy pile shows a buckling deformation behavior under the coupling effect of temperature cycles and external loads, significantly affecting the long-term serviceability and even leading to the buckling failure. To investigate the thermo-mechanical performance of end-bearing slender energy piles under the long-term effect of temperature cycles, a centrifuge modeling experiment was conducted in this work, in which the temperature distribution, displacement, axial force, and bending moment of the energy pile during the long-term temperature cycle were measured. The results unveiled that the axial force of the end-bearing slender pile increases as temperature rises, potentially leading to a displacement neutral point in the lower part of the pile. Meanwhile, there was an embedding effect in the lower part of the slender pile, with a preliminary calculated embedment depth of 36.2 m. Temperature fluctuations can soften the soil at the pile end over time, diminishing the embedding effect on slender piles, and causing a reverse bending point to emerge at a depth of 45.5 m. The appearance of bending moments in the pile signaled the horizontal displacement encountered in the pile service life, warning the bearing capacity loss problem from changes in pile deflection.

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: none
Teacher disagreement score0.633
Threshold uncertainty score0.689

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 head0.007
GPT teacher head0.185
Teacher spread0.177 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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