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Record W3166292379 · doi:10.31399/asm.cp.itsc2021p0765

Thermally Sprayed Coating-Based Heating Systems for Boundary Layer Transition Detection — An Experimental Approach

2021· article· en· W3166292379 on OpenAlexaff
M. Machulla, Shahed Taghian Dehaghani, P. Claußnitzer, S. Scheitz, André McDonald, Christoph Leyens

Bibliographic record

VenueThermal spray · 2021
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceLaminar flowComposite materialBoundary layerTransition pointCoatingStagnation pointTurbulenceAerodynamic heatingHeat transferMechanics

Abstract

fetched live from OpenAlex

Abstract Boundary layers on surfaces will change from laminar to turbulent flow after a critical length. Due to the differing heat transfer coefficients of laminar and turbulent flow, the point of transition can be detected by heating the surface and measuring surface temperature by thermographic imaging. Locating the transition point is crucial for the aerodynamic optimization of components. In this study, fiber reinforced polymer composites (FRPCs) were chosen as the test substrate. Experiments were conducted using the flame spray process and NiCrAlY coatings. Multilayered coatings consisting of an aluminum bond coat, a layer of alumina as electrical insulation, and a heating layer of titania were fabricated by atmospheric plasma spraying. Free-flight tests were conducted with a functionalized winglet in order to assess the ability of thermally-sprayed heating elements to detect the location of transition of the flow regime. The results showed that the thermally-sprayed elements heat surfaces uniformly, with sufficient radiation losses for thermographic imaging. It was also shown that the change in temperature at the point of transition was readily observable using thermography.

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 categoriesMeta-epidemiology (narrow)
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 score0.378
Threshold uncertainty score1.000

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 head0.024
GPT teacher head0.240
Teacher spread0.216 · 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.

Study designBench or experimental
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
Published2021
Admission routes1
Has abstractyes

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