Investigation of Cyclic Thermo-mechanical Interactions in Pile Groups under Varying Thermal Loading
Bibliographic record
Abstract
In this study, numerical investigations were performed to examine the thermo-mechanical characteristics of the geothermal pile group having geothermal and conventional piles arranged under a single pile cap. The geothermal piles were subjected to varying degrees of thermal loading, over five thermal cycles of heating and cooling. The piles and pile cap were simulated to behave in a linear-elastic manner, and the soil was simulated using the Mohr-Coulomb plasticity model. The analyses were performed for the pile groups having different pile spacing. The investigation findings indicate that the interactions between piles, pile cap, and the surrounding soil become intricate due to cyclic thermal loading and unloading of the geothermal piles. The thermal consequences induced by cyclic temperature variations are more pronounced in the corner geothermal pile and the side conventional pile sustains more significant thermally induced effects than the central conventional pile. Differential cyclic pile displacements in the pile cap leads to varying load distribution among all the piles. The pile location plays a significant role in determining the uneven distribution of loads within the piles and the soil. Further, the magnitude of thermal load and thermal cycles govern the load-displacement mechanism of the pile cap, piles, and supporting soil.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".