Time-dependent interaction coefficients to quantify the settlement of energy pile groups
Bibliographic record
Abstract
The use of energy piles is facing an exponential growth due to the increasing need of exploiting sustainable energy sources. Their design implies the estimation of the displacement induced by the combined thermo-mechanical interaction between piles belonging to the same group. In this regard, the work at hand derives sets of interaction coefficients for piles subjected to thermal load in not stationary conditions, using finite difference numerical analyses. These involved pile pairs embedded in different soil types at multiple spacing, namely 2, 4, 6, 8, 10 times the pile diameter. A new dimensionless parameter is also introduced to describe the evolution with time of the interaction coefficients accounting for pile-to-pile spacing, soil thermal diffusivity, pile–soil stiffness ratio, and time. The numerical results demonstrate a strict time-dependence of the interaction coefficients that is worthy to be considered in the design practice. To this aim, a practice-oriented approach is proposed allowing to evaluate the interaction effects and thereby derive the settlement of each pile in a straightforward manner. This requires as only ingredient the settlement of the isolated energy pile at the considered time instant. The simplified approach is successfully validated against full 3D thermo-mechanical numerical analyses on pile groups including conventional and energy piles with different layouts.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".