Correction Factors for the Use of 1D Solution Methods for Dynamic Laminar Liquid Flow through Curved Tubes
Bibliographic record
Abstract
The modeling of transient flows of liquids through tubes is required for studies in water hammer, switched inertance hydraulic converters, and noise reduction in hydraulic equipment. While 3D gridded computational fluid dynamics (CFD) methods exist for the prediction of dynamic flows and pressures in these applications, they are computationally costly, and it is more common to use 1D methods such as the method of characteristics (MOC), transmission line method (TLM), or frequency domain methods. These 1D methods give good approximations of results but require many orders of magnitude less computation time. While these tubes are typically curved or coiled in practical applications, existing 1D solution methods assume straight tubes, often with unknown deviation from the curved tube solution. This paper uses CFD simulations to determine the correction factors that can be used for existing 1D methods with curved tubes. The paper also presents information that can be used to help evaluate the expected errors resulting from this approximation.
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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 | 0.002 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".