Solid particle erosion of materials for use in gas pipeline control valves
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".