Field test on thermally induced bending behaviour of energy pile adjacent to slope in a plateau area
Bibliographic record
Abstract
When energy piles serve as foundation pit support, slope anti-sliding, and foundation reinforcement near slopes, the coupling effect of horizontal loading and thermal loading needs to be considered. Studies have investigated the mechanism of axially load-bearing energy piles in symmetric environments, but analyses of the behaviour of horizontal load-bearing energy piles in complex asymmetric environments are lacking. This study investigated the thermomechanical responses of an energy pile in plateau environments, with an emphasis on slope-induced effects within cobble-dominated stratigraphic layers. By analysing hysteresis phenomena under continuous and intermittent thermal loading strategies, the evolution of temperature change and cross-sectional stresses was examined, and the corresponding bending moments were referred to. Under heating conditions, the change in the bending moment state is influenced by the combined effects of the cross-sectional temperature difference, pile–soil constraint state, and pile/soil stress state. The bending moment of the slope-proximity pile is redistributed, considering that the second-order effect caused by thermal restraint stress dominates the behaviour at the pile middle. Derived from the recoverable behaviours of the pile, the pile–soil interaction can be considered thermoelastic in this plateau area.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".