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Record W2040412590 · doi:10.1115/1.1482400

On the Accuracy of Beam-Averaged Interferometric Heat Transfer Measurements

2002· article· en· W2040412590 on OpenAlex

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

VenueJournal of Heat Transfer · 2002
Typearticle
Languageen
FieldComputer Science
TopicOptical measurement and interference techniques
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsExtrapolationHeat transferInterferometryBeam (structure)Temperature gradientOpticsTemperature measurementField (mathematics)Intensity (physics)MechanicsComputational physicsMaterials sciencePhysicsThermodynamicsMathematicsMathematical analysisMeteorology

Abstract

fetched live from OpenAlex

Laser interferometry can be used in a three dimensional temperature field to measure the average fluid temperature and heat transfer rate, integrated over the length of an experimental model. However, such measurements are inherently approximate when the surface temperature varies in the direction of the test/object beam. In this study an analysis is performed to determine the accuracy of beam-averaged heat transfer rate measurements made in ideal gases. Two analysis methods are considered. The first method is based on extrapolation of the near-wall temperature field to obtain the surface gradient. In the second method, the temperature gradient at the surface is obtained directly from the gradient of the fringe field. The results show that the intrinsic error in the measurements depends strongly upon the form and magnitude of the temperature variation in the light beam direction. Although the error in the measured heat transfer rate is shown to be small for many commonly encountered conditions, it can be greater than ten percent in extreme cases.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.313
Threshold uncertainty score0.698

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.102
GPT teacher head0.271
Teacher spread0.169 · 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