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Record W2483744022 · doi:10.31399/asm.cp.itsc2015p0836

Numerical Study of the Arc Fluctuations in DC Plasma Torch

2015· article· en· W2483744022 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

VenueThermal spray · 2015
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPlasma torchTorchPlasmaMaterials scienceThermal sprayingArc (geometry)MechanicsCoatingJet (fluid)TurbulenceAnodePlasma arc weldingMagnetic fieldMomentum (technical analysis)CorrosionMetallurgyComposite materialMechanical engineeringChemistryPhysicsElectrodeEngineeringNuclear physics

Abstract

fetched live from OpenAlex

Abstract Plasma spray technology is widely employed by industry to apply coatings on different components to protect them from corrosion, wear and high temperature environments. The gases introduced into the DC plasma torch are heated by the arc and a plasma jet exits the torch. Powders are injected into the plasma jet where they are then accelerated, heated, and melted before impacting the substrate, which is placed at some distance from the outlet of plasma spray torch. Plasma arc exhibits strong voltage fluctuations which correspond to the movement of the anode arc root attachment. Understanding the arc movement within the torch and how it affects the flow and temperature fields of the plasma jet exiting the torch is of great importance. Understanding the flow, temperature and electromagnetic fields within the DC plasma torch is extremely challenging and there is a limited number of investigations in the literature. In order to provide unique sets of surface characteristics, e.g., thermal barriers, wear and corrosion resistance, a high quality coating with appropriate combination of powder and base materials must be produced. To produce a high quality coating, powder particles should be uniformly heated and accelerated, and then deposited onto the substrate. In this paper, an unsteady 3-dimensional model of the arc movement within the plasma torch is reported. The proposed model is employed to solve electric potential and magnetic vector potential equations in addition to continuity, momentum and energy equations. The k-ε turbulence model was used to model the turbulence of the flow field inside a non-transferred DC argon plasma torch. The geometry of the torch was that of SG-100 torch (Praxair). TO study the effect of the arc length on the voltage, first a steady-state model was considered for a range of arc lengths and arc-root radii. The results of this model provided the relation between arc length and arc voltage for a set of arc root radii and given argon flow rate. Then, given voltage fluctuation profile, the unsteady, arc root attachment movement was simulated from the estimation which found from steady models. Results show that the effects of velocity and temperature fluctuations at the outlet of the torch (where the particles are injected) are not negligible and such fluctuations exceed 15% of their average values. These will in turn affect the particle heating history and will negatively impact the microstructure of the coating.

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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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score0.265

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 head0.023
GPT teacher head0.257
Teacher spread0.233 · 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