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Record W4407412384 · doi:10.2514/6.2025-2364

Vacuum Operation of Consolidated Heat Pipe (CHP) for Fission Surface Power

2025· article· en· W4407412384 on OpenAlexaff
Greeta J. Thaikattil, Christopher Barth, Daniel Goodell, James Sanzi, Marc A. Gibson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicFusion materials and technologies
Canadian institutionsGibson Energy (Canada)
Fundersnot available
KeywordsNuclear engineeringFissionMaterials scienceHeat pipeEngineeringHeat transferPhysicsNuclear physicsMechanics

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.011
GPT teacher head0.276
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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