A novel modification of vapour‐lift liquid distributor
Bibliographic record
Abstract
Abstract For upgrading the liquid distribution in a trickle‐bed reactor, the distributor is always the primary consideration. The vapour‐lift tube device, most widely used in industry, still has disadvantages like mal‐distribution to overcome. Therefore in this paper, two major modifications, that is increasing of slot numbers and opening side pores, were proposed to improve its liquid distribution performance. Cold‐flow model tests were carried out with liquid distribution, and pressure drop was measured by liquid collectors and Omega pressure sensor, respectively. The results showed that as compared with proto type, the modified liquid distributor has a better liquid distribution performance and a lower pressure drop. Liquid distribution increases with the increasing of gas/liquid velocity ratio ϵ only when it is <200. The pressure drop of new distributor increases with increasing of inner tube gas velocity and ϵ . Finally, correlations for liquid distribution and pressure drop of a new distributor were derived, showing rather good agreements with experimental results.
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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) | 0.000 | 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".