Experimental and Modeling Investigation for Slugging Pressure under Zero Net Liquid Flow in Underwater Compressed Gas Energy Storage Systems
Bibliographic record
Abstract
As an emerging flexible-scale energy storage technology, underwater compressed gas energy storage (UW-CGES) is regarded as a promising energy storage option for offshore platforms, offshore renewable energy farms, islands, coastal cities, etc. Liquid accumulation often occurs in underwater gas transmission pipelines, which is a challenge to overcome. In this study, an experimental investigation is carried out on the pressure distribution characteristics of liquid accumulation flow in hilly terrain under the condition of Zero Net Liquid Flow. A slug flow pressure model with different inclination angles at four times is established and verified, and its error range is within ±20%. Analysis revealed that reduction and growth in pressure difference are related to the outflow of slug in an inclined pipe. A high-speed camera is used to capture the movement of liquid accumulation under Zero Net Liquid Flow (ZNLF) and record the associated dynamic parameters. By imaging the motion of liquid accumulation and detecting the pressure changes in the pipeline at various times, the pressure fluctuation in the pipeline at the slug flow cause is studied. Outcomes from this work can be leveraged to help further the development of underwater compressed gas energy storage technology.
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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 | 0.000 |
| 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 | 0.001 |
| 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".