The Effect of the Pipe Bending Angle on the Pressure Losses Vane Elbow Pipes
Bibliographic record
Abstract
Pressure loss is one of the significant parameters in designing pipe bends. In this paper, the pressure distribution and pressure losses induced by turbulent flows in a circular cross-sectioned piping elbow with or without guide vane were simulated. The flow distribution in the piping elbow was simulated by the k- model using control volume method. The main objective of this study is to characterize the effect of changing the angle of pipe bend and Reynolds number on the flow separation of single-phase turbulent flow through numerical simulation. Results were validated by other experimental results and then loss coefficient was calculated in different angles from 45 to 135-degree pipe bend in various radius ratios with or without guide vane. Despite the fact that increasing pipe angle increased the pipe bend loss coefficient, using guide vane in the pipe elbow decreased this coefficient. In the radius ratio 1.5 with one guide vane, the loss coefficient of the pipe bends decreased by 50 percent in all degrees. Results revealed that the use of two vanes in pipe bend is more effective on the reduction of elbow pressure losses. Moreover, two guide vanes can decrease loss coefficient more than 50 percent. Also, the results indicated that loss coefficient decreased by increasing Reynolds number.
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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 | 0.000 | 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 | 0.001 |
| 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".