Numerical Simulation of the Erosion Phenomenon at the Knee Tube at Different Angles Using DOE Method
Bibliographic record
Abstract
This numerical study is considered to investigate the erosion in the pipeline systems affected by different parameters such as elbow angle and type, mass flow rate, pipe radius, and wall materials using Computational Fluid Dynamics (CFD). the gravity effect has been considered along the Y-direction. The Standard k- model has been selected for turbulence, and standard wall functions have been used for near-wall treatment. Discrete phase modelling (DPM) is selected to model the secondary phase (sand particles). The continuous phase is crude oil, and the discrete phase is sand. The particle characteristics were selected based on the region of Saudi Arabia. Validations are conducted based on the maximum erosion rate at different inlet velocities and particle sizes. Four different elbow angles included 90, 60, 45, and 30 degrees and two types of elbow included sharp and smooth elbow was used to study the behaviour of the erosion rate. The roughness height is selected to introduce the wall material; considering that, each material has a specific roughness height. Therefore, the recognition of every material in this study is done by roughness height. Three parameters of the mass flow rate, tube radius, and roughness height are considered as input parameters to perform the DOE. The DOE study showed that the pipe radius has the most effect on the erosion rate. The reason rate in the Generic models for different angles with curvature(5D) 90,60,45,30 are 5.6 10 -10 , 2.7 10 -10 , 1.5 10 -9 , 3.96 10 -10 respectively.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".