Steady-State Segmented Thermofluid Network Simulations of a Loop Heat Pipe Operating With Four Different Working Fluids
Bibliographic record
Abstract
A segmented network thermofluid model for the simulation of a loop heat pipe (LHP) operating under steady-state conditions is presented, with special emphasis on quasi one-dimensional models and semi-empirical correlations for the related multiphase phenomena. Attention is focused on an LHP with one flat-evaporator, a vapor transport line, one condenser, a liquid transport line, and a compensation chamber. The evaporator consists of the following parts: An upper piece, machined out of a stainless steel plate, with vapor-transport grooves of rectangular cross section on its bottom face; a lower piece, also machined out of a stainless steel plate, with a cavity of rectangular cross section that serves as the liquid pool in the evaporator during the operation of the LHP; and a rectangular wick sandwiched between the upper and lower pieces. The wick is a sintered powder metal plate made of stainless steel. The condenser is a horizontal tube that is fitted with excellent thermal contact inside a large high thermal conductivity metallic sleeve that is maintained at a fixed sink temperature. The vapor-transport line, the condenser, and the liquid-transport line are divided into control volumes or cells. Quasi one-dimensional models are used to impose balances of mass, momentum, and energy on each of these cells. The variation of fluid thermophysical properties and multiphase phenomena, such as the change in quality and pressure drops in the two-phase regions, are suitably accounted for in this model. Four different working fluids, ammonia, distilled water, ethanol and isopropanol, are considered, and the results obtained for a representative range of steady-state operating conditions of the LHP are presented and comparatively discussed.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".