Load–displacement response and interaction behavior of energy pile groups under combined mechanical and cyclic thermal loading
Bibliographic record
Abstract
Energy piles are regarded as an innovative technology that can be deployed as groups to provide structural support and geothermal energy for buildings. This study aims to investigate the load–displacement response and the interaction behavior of energy pile groups under combined thermomechanical loads. An analytical approach was developed for the thermomechanical analysis of grouped energy piles and validated against experimental data. The approach was further adopted to evaluate the effects of load levels, pile geometries, and soil–pile interface characteristics on the pile-to-pile interaction. Then, the displacement behavior of grouped piles under typical thermomechanical load paths (i.e., subjected to stepwise mechanical loads first and then cyclic thermal loads) was investigated. The results show that increasing thermomechanical load levels will decrease the displacement interaction factor between energy piles. The effects of load levels on the pile-to-pile interaction become more significant with increasing slenderness ratio. Besides, the cyclic thermal loads may cause the irreversible displacement response of energy pile groups. Due to the group action effects, the grouped energy piles experience more significant settlement than single piles after thermomechanical load paths. These results highlight the significance of accounting for the pile-to-pile interaction and the soil–pile interface behavior when addressing energy pile groups.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".