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Record W4255348006 · doi:10.32920/ryerson.14646372

Numerical Simulation Of Thermodiffusion Subjected To Different Gravity Fields

2021· preprint· en· W4255348006 on OpenAlexaff
Ahmad Khoshnevis

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicField-Flow Fractionation Techniques
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsBuoyancyMechanicsConvectionAmplitudeDiffusionComputational fluid dynamicsResidualWork (physics)Rayleigh scatteringPhysicsFlow (mathematics)ThermodynamicsMathematicsOptics

Abstract

fetched live from OpenAlex

In this work, a typical thermodiffusion experiment on a binary mixture is simulated numerically using a two-dimensional computational fluid dynamics (CFD) code. Three scenarios for gravity have been studied: residual, pure oscillatory, and microgravity micro-accelerations. It was found that less separation of mixture components in the presence of strong gravity fields is due to the formation of buoyancy-driven flows. For the case of pure oscillatory gravity, the effects of the frequency and amplitude are discussed in detail. A critical vibrational Rayleigh number is proposed above which the diffusion process is highly affected by the external excitation. For the case of the microgravity environment, quasi-steady accelerations and g-jitter, both of which are found on the International Space Station, have been considered. Results show g-jitter has a minimal effect on the thermodiffusion experiment. The effects of the residual gravity field were also found to be insignificant in stimulating a strong convection flow.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.515
Threshold uncertainty score0.740

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)0.0010.000

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 head0.015
GPT teacher head0.262
Teacher spread0.248 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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