Comparison of 2D and 3D Predictions of Erosion Wear in Centrifugal Slurry Pump Casings
Bibliographic record
Abstract
This paper deals with the prediction of erosion wear rate in slurry pump casings, with an emphasis on the comparison of two-dimensional and three-dimensional results. The two-dimensional analysis is carried out in the mid-plane of the pump normal to the pump axis. The dense solid-liquid flow field in the pump casing is modeled using an Eulerian-Eulerian model with a penalized finite element formulation to discretize the continuum equations. Erosion wear due to particle impact and sliding abrasion depends on the local velocity, shear stress, concentration of the particles and the empirically determined (particle-size dependent) wear rate coefficients used to relate the erosion wear to the local flow field properties.The wear rate predictions from the 2D and 3D codes are compared to analyze the three dimensional flow effects on the wear rate. Operating conditions under which the 2D solution departs significantly from the 3D solution are explored with the aim of determining the limitations of the 2D simulations. Three pumps with different casing width-to-depth ratio are analyzed. Flow conditions and the pump casing width-to-depth ratio affect the differences between the 2D and 3D casing wear predictions.Copyright © 2013 by ASME
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".