Performance Characterisation and Cavitation Detection of Variably Angled V-Shaped Opening Ball Valves
Bibliographic record
Abstract
The objectives of this thesis are to characterise the performance of variably angled V-shaped opening ball valves in terms of pressure drop and cavitation. Both numerical and experimental techniques are utilised here to study the effects of apex angle of the V-opening on pressure drop and cavitation characteristics. Three different ball sizes are used to investigate scalability of the V-ball valves in terms of cavitation inception and pressure coefficient. The results of the pressure drop experiments show that as the size of the ball and the apex angle of the valve increases, the pressure coefficient tends towards a constant value. This means that larger V-opening ball valves can be scaled using pressure coefficient within 15%. It has been well established that cavitation causes high frequency noise. Therefore dynamic pressure transducers were used to detect acoustic cavitation noise by considering the high energy content in the 2 kHz to 45 kHz frequency band. To measure the energy levels, spectral analysis was performed and the power spectrum density was acquired using fast Fourier transform algorithm and the area under the curve was integrated in three different frequency intervals of 2 to 5 kHz, 5 to 10 kHz and 10 to 45 kHz to capture the frequency band at which cavitation onset occurs. This energy was compared to the reference energy levels in the same frequency intervals when no valve was installed. Two criteria were chosen to represent a cavitating flow, the first criteria was the start of a steep exponential increase in the energy from the reference energy in at least one of the frequency ranges defined and the second criteria is an increase in the coherence function in any of the three frequency ranges. This procedure was performed for all valves tested at 10% opening increments starting at fully open position and the inception cavitation number was recorded to define the onset of cavitation. It was observed that as the apex angle decreases, cavitation number also decreases where the size of the valve did not affect cavitation number. The conclusion was that as the opening decreases, cavitation inception occurs at higher pressure drops. However some deviations from this general trend were observed. These deviations are perhaps due to the turbulent structures such as flow separation and vortices, suggested by the pressure fluctuations in the static pressure. Finally numerical modelling of 1 inch 60V valves were performed using ANSYS Fluent computational fluid dynamics (CFD) software for three openings using two different turbulence models, standard k-ε and SST k-ω. The results were contrasted against the experimental data to evaluate which model performs the best for this application. From the results obtained, standard k-ε predicts the pressure drop within 15% of the experimental data. Also flow separation is a major cause of high local pressure drops and therefore cavitation and SST k-ω predicts cavitation better than standard k-ε. This is due to better performance of SST k-ω at predicting turbulence characteristics of flow separation region.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".