On the hydrostatic limit for thin film flow with applications to thermosyphons
Bibliographic record
Abstract
Heat pipes frequently encounter challenges in effectively returning condensed liquid from the condenser to the evaporator through capillary pumping, which limits their overall efficacy. When capillary pumping becomes irrelevant due to factors like an absent wick or overfilling, the heat pipe is more properly termed a thermosyphon. In a close-to-horizontal orientation, the driving force for liquid return in a thermosyphon relies on the difference in liquid pool depth between the evaporator and condenser. An excessively deep liquid pool in the condenser can hinder radial heat transfer, necessitating a design that favors intermediate-depth liquid pools. This study utilizes a theoretical approach based on the lubrication approximation to the Navier–Stokes equations to determine the fill ratio that maximizes thermosyphon performance. We explore the relationship between this fill ratio and factors such as the axial temperature difference along the thermosyphon. Our analysis thereby highlights the hydrostatic-driven flow limit in the thermosyphon as an analogue to the capillary limit in heat pipes. Regarding the hydrostatic limiting curve as an alternative to the capillary limiting curve offers valuable insights for enhancing thermosyphon performance and provides a means of comparing the performance of one vs. the other passive heat transfer device.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".