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Record W4391329865 · doi:10.2514/6.2024-2524

Thermal Environment Provided by a High-Altitude Balloon Payload Shielded from Terrestrial Radiation

2024· article· en· W4391329865 on OpenAlexaff
Arnab Sinha, Caileigh Bates, Xavier Duchesne, Mathias N. Larrouturou, Andrew Higgins

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerospace Engineering and Energy Systems
Canadian institutionsMcGill University
Fundersnot available
KeywordsPayload (computing)Shielded cableBalloonAerospace engineeringEnvironmental scienceRadiationEffects of high altitude on humansAstrobiologyComputer scienceEngineeringPhysicsElectrical engineeringMeteorologyOpticsMedicine

Abstract

fetched live from OpenAlex

The thermal environment provided by a high-altitude balloon payload that is shielded from the thermal radiation emitted by the earth is investigated. If launched at night and to a sufficient altitude wherein radiative heat transfer determines the payload thermal environment, such a shielded payload may reach radiative equilibrium with the effective sky temperature in the nighttime stratosphere. Then, in principle, extremely low temperatures may be achieved. The objective is to analyze the feasibility of using High-Altitude Balloons for spacecraft systems testing in low pressure and low temperature environments. In this study, a heat transfer model was developed to study the thermal environment of a balloon-borne radiation shield in the stratosphere. Also, theoretical models of balloon ascent rate were developed to define optimal launch parameters. Three flight predictors were used to narrow the possible landing locations and improve the probability of successful recovery. Five experimental payloads were flown to the stratosphere and successfully recovered for data analysis. The obtained flight results appear to indicate that the expected trend of radiation cooling is observed.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.004
GPT teacher head0.164
Teacher spread0.160 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2024
Admission routes1
Has abstractyes

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