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Record W6910504814 · doi:10.4050/f-0071-2015-10136

Assessment of CFD/CSD Analytical Tools for Improved Rotor Loads

2015· article· en· W6910504814 on OpenAlexaff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAeroelasticity and Vibration Control
Canadian institutionsBell Helicopter Textron (Canada)
Fundersnot available
KeywordsTorsion (gastropod)Lift (data mining)Wind tunnelHelicopter rotorRotor (electric)Bending

Abstract

fetched live from OpenAlex

Comparisons of many analysis codes have been made during the course of the UH-60 Airloads Workshops. However, most comparisons involve only a small number of codes, and modeling assumptions are not consistent among all researchers. The Improved Prediction of Rotor Loads TAJI project, funded by the Vertical Lift Consortium (VLC), was initiated in part to perform a rigorous comparison of coupled solutions with the most widely used CSD and CFD codes. Careful comparisons of the structural models were made, and small modeling differences were eliminated. Loosely coupled simulations were made for UH-60A flight and wind tunnel test cases, in addition to other industry helicopter configurations. Flap bending and blade torsion loads are well predicted for all of the cases studied, while edgewise bending and pushrod loads tend to contain higher harmonic load content, which is less well predicted by the analysis. The various code combinations studied yield very similar load predictions when identical modeling assumptions are made. However, certain gaps remain in terms of correlation with test data.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.974
Threshold uncertainty score0.234

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 head0.045
GPT teacher head0.299
Teacher spread0.253 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2015
Admission routes1
Has abstractyes

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