Experimental Investigation Into Bulk Performance of Three Different Style Inline Separators on Natural Gas at High Pressure, Different Liquid Loadings and Gas Flows
Bibliographic record
Abstract
Abstract Inline vertical separators are commonly employed on natural gas transmission facilities (e.g., receipt stations) to primarily filter out liquid contaminants such as compressor oil, glycol, free water, etc. However, these contaminants have been found invariably in the piping system downstream of these separators, indicating the separators are not performing as required. The potential consequences of not removing such contaminants includes lower gas quality, impaired gas metering accuracy, corrosion and damage to equipment/instrumentation and adverse impact on industrial or residential end users. Historically, separators’ performance claims and guarantees in terms of efficiency of liquid removal are often of the order 98–99% of liquid droplet sizes ≥ 8μm. However, there is a lack of ability to verify these claims due to difficulties in quantifying liquid injection rates and droplet characteristics vs. liquid collected while in operation. Extensive testing was undertaken at TC Energy’s Gas Dynamic Test Facility in Didsbury, Canada on three different separators from different manufacturers, two are mesh vane type (MV-1 and MV-2), and the third is dual cyclonic type (DC). The tests were conducted in the range of 4–5 MPa and flow velocity in the range of 1.3–13 m/s in the DN150 inlet nozzle to the separator, i.e., at 10:1 turn down ratio. The injected liquid was industrial compressor oil, typically used in the gas transmission industry, and was injected at a loading in the range of 0. 06–1.8%. Four different spray nozzles were used to atomize the injected oil to a range of particle size distributions (PSD), characterized by median diameter size, D50, in the range of 50–90 μm. Test results revealed that the performance of these separators varied between 90–99.8% independent of liquid loading. The effective Souders-Brown K factor also varied between 0.15–0.27 m/s. Tests were also conducted following a batch of solid injection to determine the effects on liquid separation efficiency on MV-2 separator. It was found that the separation efficiency decreased by approximately 9% following a 7.075 kg batch of solid injection, likely due to the accumulation of solids in the vane-pack.
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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 | 0.001 | 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 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".