Ground Heat Transfer From a Varying Line Source With Seasonal Temperature Fluctuations
Bibliographic record
Abstract
In this paper, transient heat conduction between a line heat source and a semi-infinite medium (representing a foundation of a power transmission tower and the surrounding ground) is analyzed numerically and experimentally. The tower foundation is represented by a metal rod buried in a semi-infinite medium. Using an experimental test cell with a data acquisition system, heat transfer and temperature measurements within the domain are collected. The experimental studies are first applied to unidirectional heat conduction, wherein the analytical solutions are compared against measured temperature responses. Then two transient heat transfer cases are studied: one case with a steady heat input provided by an electrical heater and another with sinusoidal temperature variations achieved by temperature-controlled fluid in a heat exchanger. The analysis shows that a metal tower footing has significant thermal effects on the temperature response of the local half-space around the footing in the foundation. This thermal effect varies with time, as well as spatially at different positions around the tower footing. In particular, measured results from the case of sinusoidal temperature variations show that the tower footing introduces additional temperature increases in the “summer” periods and temperature decreases in the “winter” periods.
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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 | 0.000 | 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) | 0.001 | 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".