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Reply to “Comment on ‘Evolution of wall shear stress with Reynolds number in fully developed turbulent channel flow experiments' ”

2020· article· en· W3117180905 on OpenAlexaff
Pierre-Alain Gubian, Jordan Stoker, James I. Medvescek, Laurent Mydlarski, B. R. Baliga

Bibliographic record

VenuePhysical Review Fluids · 2020
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsMcGill University
Fundersnot available
KeywordsReynolds numberTurbulencePhysicsReynolds stressShear stressMechanics

Abstract

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\"Orl\"u and Schlatter [R. \"Orl\"u and P. Schlatter, preceding Comment, Phys. Rev. Fluids 5, 127601 (2020)] claim that the evolution of the turbulent intensity of the wall-shear stress (${\ensuremath{\tau}}_{{w}_{RMS}}/\ensuremath{\langle}{\ensuremath{\tau}}_{w}\ensuremath{\rangle}$) to a constant value at sufficiently large Reynolds number in our previous work [P.-A. Gubian et al., Phys. Rev. Fluids 4, 074606 (2019)] is the result of ``strong effects of insufficient spatial resolution'' of the sensor used therein, which, when corrected for, restores a continual Reynolds number dependence of ${\ensuremath{\tau}}_{{w}_{RMS}}/\ensuremath{\langle}{\ensuremath{\tau}}_{w}\ensuremath{\rangle}$. They also argue that the temporal resolution of the sensor used in our work had not been characterized. Herein, it is demonstrated that there are multiple other studies that have shown (by way of direct numerical simulation) that ${\ensuremath{\tau}}_{{w}_{RMS}}/\ensuremath{\langle}{\ensuremath{\tau}}_{w}\ensuremath{\rangle}$ becomes constant and independent of Reynolds number. Moreover, as \"Orl\"u and Schlatter themselves note, their proposed correction substantially overcorrects the data, such that the corrected data are ``too high and strong,'' which is presumably because they are applying a correction designed for velocity measurements to a sensor that (directly) measures wall-shear stress and is governed by different physical principles. Finally, the frequency response of the sensor used in our previous work (a flush-mounted hot-wire sensor in which the hot-wire is installed over a small rectangular cavity in the base of the sensor) has indeed been characterized and documented, by Sturzebecher et al. [D. Sturzebecher et al., Exp. Fluids 31, 294 (2001)]. Therein, the sensor was shown to have a cutoff frequency that exceeds 30 kHz, whereas the highest frequencies of the flow in our previous work did not exceed 10 kHz.

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)0.007
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.046
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.029
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0050.006
Scholarly communication0.0030.005
Open science0.0060.003
Research integrity0.0460.049
Insufficient payload (model declined to judge)0.0100.017

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 head0.016
GPT teacher head0.255
Teacher spread0.239 · 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 designNot applicable
Domainnot available
GenreCommentary

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".

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Citations1
Published2020
Admission routes1
Has abstractyes

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