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Record W3212567276 · doi:10.32920/ryerson.14647734.v1

Solid particle erosion of materials for use in gas pipeline control valves

2021· preprint· en· W3212567276 on OpenAlexaff
Ehsan Akbarzadeh

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicErosion and Abrasive Machining
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMaterials scienceTungsten carbideScanning electron microscopeTungstenBrittlenessStelliteErosionMetallurgyParticle (ecology)AbrasiveComposite materialMicrostructure

Abstract

fetched live from OpenAlex

To aid in the materials selection of gas control valves, the solid particle erosion behaviour of twelve metals was investigated using impinging jets of magnetite particles. The erosion rates were measured for two different particle sizes, two different velocities, and six different impingement angles. Scanning electron micrography and EDX (Energy Dispersive X-ray analysis) mapping was used to investigate the erosion mechanisms and the extent of particle embedding. There was no measurable erosion for the Tungsten Carbide samples, even for very long exposure times. For nickel plated steel, the plating was found to delaminate, resulting in a brittle erosive response. For all other tested materials, the measured erosion rates and scanning electron micrographs indicated a ductile erosion mechanism under all conditions considered. The erosion rates were found to fit a semi-empirical erosion model due to Oka et al. [1] well. The most erosion resistant materials were found to be the Solid tungsten carbide (WC) and Solid Stellite 12 and the least erosion resistant materials were A1018 carbon steel nickel plated and A240 Type 410 stainless steel plate. With all other conditions being equal, a larger erosion rate was measured when utilizing the smaller particles, than when the large particles were used. This counter-intuitive result was demonstrated to be due to a combination of effects, including the formation of thicker hardened layer more embedded particles, and more particle fragmentation when utilizing the larger particles.

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 categoriesInsufficient payload (model declined to judge)
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 score0.034
Threshold uncertainty score0.998

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)0.0030.000

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 head0.032
GPT teacher head0.302
Teacher spread0.270 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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