Thermodynamic modeling of thermosyphons and heat pipes
Bibliographic record
Abstract
A model capable of predicting the thermodynamic state of the working fluid and its related properties inside a thermosyphon and a heat pipe is proposed. The model theoretically analyzes the entropy changes of various thermodynamic processes and determines the possible locations of the state points on a temperature-specific entropy (T-s) and a specific enthalpy-specific entropy (h-s) diagram at each stage of the thermodynamic cycle. The analysis reveals that the working fluid enters the condenser in a superheated state, while it enters the evaporator in a subcooled state, irrespective of the operating conditions. Analytical expressions are derived to predict the changes in the temperature, pressure, specific volume, entropy, and enthalpy during each thermodynamic process, along with expressions for estimating entropy generation. The effects of varying input heating power (Qiṅ), the fill ratio, the device aspect ratio, and the device inclination angle (θ) on the working fluid behavior are examined, revealing that they affect the thermodynamic state of the working fluid during operation. The conclusion drawn in the existing heat pipe literature that the operating parameters only influence the thermal resistance of thermosyphons and heat pipes is, therefore, incomplete. The geometric and the operational parameters influence the state of the working fluid at each stage of the thermodynamic cycle. The present thermodynamic model, in conjunction with existing heat pipe theory, completely describes thermosyphon and heat pipe operation under any given set of conditions.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".