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Record W3089678210 · doi:10.1002/htj.21958

Heat transfer analysis of inclined magnetic field and activation energy in Maxwell nanofluid with thermophoresis effects

2020· article· en· W3089678210 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

VenueHeat Transfer · 2020
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsFanshawe College
Fundersnot available
KeywordsThermophoresisNanofluidBiot numberHeat transferMechanicsPrandtl numberMagnetic fieldPartial differential equationPhysicsClassical mechanicsThermodynamics

Abstract

fetched live from OpenAlex

Abstract Numerical analysis is performed for incompressible Maxwell nanofluid model flow under the implications of thermophoresis and inclined magnetic field over a convectively stretched surface. The system that comprises differential equations of partial derivatives is remodeled into the system of ordinary differential equations via similarity transformations and then solved through by Runge–Kutta–Fehlberg with shooting technique. The physical parameters, which emerge from the derived system, are discussed in graphical formats. Excellent proficiency in the numerical process is analyzed by comparing the results with available literature in limiting scenarios. The significant outcomes of the current investigation are that the velocity field decays for higher fluid parameters while that peter out the fluid temperature. Further, the heat transfer rate is reduced with the incremental values of fluid and thermophoresis parameters while it uplifts with Biot and Prandtl numbers.

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 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 score0.076
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.180
Teacher spread0.174 · 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