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Record W4403217575 · doi:10.3390/ma17194915

Using the Ethaline Electropolishing Method on the Internal Surface of Additive Manufactured Tubes

2024· article· en· W4403217575 on OpenAlexaff
Dongyi Zou, Chaojiang Li, Yuxin Yang, Xin Jin, Shenggui Liu, Hongyi Zhang, Na Zhang

Bibliographic record

VenueMaterials · 2024
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsUniversity of Alberta
FundersNational Natural Science Foundation of China
KeywordsElectropolishingMaterials scienceSurface (topology)Composite materialChemistryGeometryMathematicsElectrode

Abstract

fetched live from OpenAlex

Electropolishing is a widely used technique for polishing additive manufactured (AM) components, while complex internal surface polishing remains a challenge. In this study, we explore the use of ethaline as an electrolyte and investigate the effects of temperature, time, stirring speed, and voltage on the electropolishing effectiveness for AM tubes without pre-treatment through orthogonal experiments. The optimal combination of these factors is then applied in further electropolishing experiments on straight tubes with large length-to-diameter ratios and an angled tube. Our results indicate that temperature has the most significant impact on internal surface electropolishing performance, and other factors' effects are also analyzed. Ethaline can be a promising electrolyte for internal surface electropolishing of AM components because of its high viscosity, which is validated by flow field simulation of the hydrodynamic conditions inside the tubes.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.031
GPT teacher head0.294
Teacher spread0.263 · 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 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

Citations4
Published2024
Admission routes1
Has abstractyes

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