Numerical Analysis of Newtonian Fluid Flow Through Multi-Hole Orifice Meter
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The influence of multi-hole orifice flow meter geometry parameters on the parameters of Newtonian fluid through multihole orifice meters was investigated using computational fluid dynamics as well as the effect of contamination in front of the MHO flow meter.The air flow was steady, three-dimensional, and turbulent.Analysed Newtonian fluid was air and physical properties that were considered were density and dynamic viscosity.The numerical method was finite volume method, and standard k-ε turbulence model was used for turbulence modelling.Multi-hole orifice meter with three different β parameters 0.55, 0.6 and 0.7, was observed and Reynold's number was 10 5 .The pressure drop and discharge coefficient were analysed.Numerical simulations were performed using commercial software the STAR-CCM+ 2019.2.It was found that increase in parameter results with the decrease in pressure drop and increase in discharge coefficient.Also, it was found that that the influence of parameter is much higher when analyzing pressure drop rather than discharge coefficient values.Numerical simulations were also performed to investigate the effect of contaminations in front of the MHO plate with = 0.5, on the discharge coefficients.It was found that as the contamination angle is increased the discharge coefficient tends to increase.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it