Cyclic t-z model for the long-term thermomechanical analysis of energy piles
Bibliographic record
Abstract
Many elastoplastic and nonlinear models have simulated the long-term behavior of energy piles under cyclic thermomechanical loads. Although they considered the strain–stress hysteretic relationship at the pile–soil interface, the interface strength was assumed independent of the number of thermomechanical cycles. This simplification may cause errors in predicting the long-term responses of energy piles. Therefore, we proposed a cyclic t-z model for the long-term thermomechanical analysis of an energy pile. Here, the interface strength of the model changes with the cycle number of thermomechanical loads. In addition, the accumulation of irreversible deformation at the pile–soil interface can be modeled. Moreover, the cyclic performance of interface shear tests and the long-term behavior of an in situ energy pile were simulated. Comparisons between the measured and simulated results indicated several vital aspects of the energy pile–soil interaction, including strength degradation, strain ratcheting phenomenon of the interface, and long-term pile responses under cyclic thermomechanical loading. Furthermore, numerical simulations were used to evaluate the effects of model parameters on the long-term behavior of energy piles under thermomechanical loads.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".