Vacuum Operation of Consolidated Heat Pipe (CHP) for Fission Surface Power
Bibliographic record
Abstract
Consolidated Heat Pipe (CHP) is a new technology that enables direct thermal power delivery to the hot-end of a Stirling engine using a heat pipe- a two phase passive heat transfer device. CHP was developed after the efforts of the Kilopower Using Stirling TechnologY (KRUSTY) test where a heat pipe was used to deliver thermal power from a fission-based reactor to a Stirling engine to produce 1 kWe of useable electrical power in 2018. Large thermal losses were noted during the KRUSTY test where a temperature drop of 145 °C was measured between the heat pipe’s condenser and the engine’s hot-end. The Consolidated Heat Pipe was designed to address and mitigate this temperature loss. CHP was designed, built and tested at the Glenn Research Center (GRC). The initial test was performed in ambient air conditions, and the results were presented in “Consolidation of a Sodium Heat Pipe and Stirling Engine for Fission Surface Power” at the Thermal Fluids Analysis Workshop in 2023. Researchers at GRC have tested this technology again in a vacuum environment in 2024. Results show that the heat pipe and the hot-end of the Stirling engine are isothermal with a minimal temperature differential of approximately 2.5 °C in varying operational states. The Consolidated Heat Pipe technology has proven to be an efficient way of delivering thermal power directly to Stirling engines.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".