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Record W2998053728 · doi:10.2514/6.2020-0311

Design and Testing of 3-D Riblets

2020· article· en· W2998053728 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

VenueAIAA Scitech 2020 Forum · 2020
Typearticle
Languageen
FieldEngineering
TopicMechanical Engineering and Vibrations Research
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

This paper describes wind tunnel experiments conducted on conventional riblets and riblets with gradual streamwise ridge height variation, known as ‘3-D’ riblets. Riblets are V-shaped or blade-type grooves with height and spacing between peaks of .002 to .005 inches, depending on conditions. The goal of 3-D riblet designs is to modify the flow topology in a manner similar to conventional riblets but with reduced wetted area, thereby achieving a larger drag reduction. Several design variables were defined and conventional 2-D and 3-D riblet panels were produced to enable evaluation of the impact of each variable. Wind tunnel results for all the riblet designs tested are compared to smooth surface results. This work complements computational analysis that predicted promising drag reduction improvements for some 3-D designs but also indicated that the drag savings were highly sensitive to geometric imprecision. Wind tunnel results and metrology confirmed this sensitivity.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.925
Threshold uncertainty score0.307

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 head0.039
GPT teacher head0.238
Teacher spread0.199 · 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