Numerical Simulation of a Cylindrical Heat Pipe and Performance Study
Bibliographic record
Abstract
Heat Pipes are passive devices used for transferring heat from a heat source to a heat sink with very small difference in temperature. They have three main sections namely the evaporator, adiabatic section and the condenser. In construction terms, they have three parts, the metal container, the porous wick region which lines the container from inside and the hollow flow chamber. Heat pipe performance is governed by several parameters such as the geometry, dimensions, working fluid, wick and container materials etc. In this study numerical simulation method was used to analyze the performance of the heat pipe. A numerical model based on Navier stokes equation, Energy equation and conjugate heat transfer was developed using COMSOL Multiphysics package. The top wall temperature profile obtained was validated with experimental results, and further the absolute thermal resistance was calculated. A sensitivity study was carried out to study the performance dependency of heat pipe on four parameters namely, porosity, condenser evaporator lengths, radius of heat pipe and the heat input, in terms of the absolute thermal resistance. The results showed that absolute thermal resistance varied directly with respect to porosity of the wick, and inversely in case of radius of the heat pipe. The absolute thermal resistance was maximum in case of equal condenser and evaporator lengths. Interestingly the absolute thermal resistance did not vary with the applied heat rate, demonstrating the practicality in using absolute thermal resistance as a performance characteristic parameter.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".