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Record W2095518229 · doi:10.1119/1.3685117

Maximum Aerodynamic Force on an Ascending Space Vehicle

2012· article· en· W2095518229 on OpenAlex
Philip Backman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Physics Teacher · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicExperimental and Theoretical Physics Studies
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsSpace ShuttleSpacecraftAerodynamicsAerospace engineeringThrustAccelerationSpace vehicleAeronauticsDynamic pressureBandwidth throttlingPhysicsComputer scienceEngineering

Abstract

fetched live from OpenAlex

The March 2010 issue of The Physics Teacher includes a great article by Metz and Stinner on the kinematics and dynamics of a space shuttle launch.1 Within those pages is a brief mention of an event known in the language of the National Aeronautics and Space Administration (NASA) as “maximum dynamic pressure” (called simply “Max.AirPressure” in the article), where the combined effect of air density and the shuttles speed produce the greatest aerodynamic stress on the vehicle as it ascends through the atmosphere toward orbit. Official commentary during a launch2 refers to this point in the ascent with language such as “space shuttle main engines throttling back as vehicle enters area of maximum dynamic pressure” and occurs in a range between 45 and 60 s after launch. (In dealing with this stress, the space shuttles main engines reduce their thrust at approximately 45 s to reduce acceleration, and return to normal levels again some 15 s later as maximum dynamic pressure is traversed.) This paper presents an analysis, accessible to introductory-level students, that predicts the time of Max. AirPressure for a given ascending spacecraft.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.346
Threshold uncertainty score0.552

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)0.0000.000

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 head0.014
GPT teacher head0.272
Teacher spread0.258 · 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