Experimental characterization of neon pulsating heat pipes for cryocooler-based HTS magnets
Bibliographic record
Abstract
Pulsating heat pipes (PHPs), i.e. passive devices employing two-phase flow, are increasingly studied in cryogenic conditions to improve heat transfer between cryocoolers and high temperature superconducting (HTS) magnets. This paper presents the experimental characterization of PHPs tested in vertical orientation using neon as working fluid. The main objective is to carry out a parametric study to assess the optimum parameters for a potential application to the cooling of HTS magnets. A summary of the literature on PHPs experiments under cryogenic conditions justifies the choice of neon as the working fluid for this specific application. It also leads to the selection of high-performance PHP designs for the parametric study. The PHP designs, the experimental setup, procedures, and campaigns are described. The results of the individual characterization of two PHPs, having 5 and 10 turns respectively, are analyzed and their performances are compared. In addition, a specific configuration operating simultaneously two 5-turn PHPs in parallel is investigated. The experiments are performed for two condenser temperatures (27 and ), a wide range of filling ratios (15 to 90%) and of heat loads (2 to ). The effect of the number of turns and the series or parallel configuration on the thermal performance is quantified and discussed, along with the effect of condenser temperature, filling ratio and heat load. The optimum parameters are found to be the two 5-turn PHPs in parallel, the filling ratio of 35% and the condenser temperature of . These conditions lead to the lowest evaporator temperatures with thermal resistances ranging from 0.15 to , while keeping a reliable working stability and no dry-out phenomena occurrence in the heat load range tested.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".