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Record W2810105318 · doi:10.1002/cjce.23292

Experimental investigation on pressure drop of a laboratory‐scale random packing column under roll and heave motion

2018· article· en· W2810105318 on OpenAlexvenueno aff
Yi Huang, Xiaoning Di, Jun Ma, Shujie Chen, Wenhua Wang

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
FundersCollaborative Innovation Center of Major Machine Manufacturing in LiaoningMinistry of Industry and Information Technology of the People's Republic of ChinaNational Natural Science Foundation of China
KeywordsDrop (telecommunication)Pressure dropMechanicsTilt (camera)Ambient pressureLiquid dropMaterials scienceGeologyStructural engineeringPhysicsEngineeringMeteorologyMechanical engineering

Abstract

fetched live from OpenAlex

Abstract The effects of tilt, roll, and heave ship motion on pressure drop were investigated in a laboratory‐scale random packing, which was located at a six degree of freedom (6DoF) motion parallel platform. The water‐air system was adopted, and various operating condition (liquid load and F‐factor) as well as sea states were tested. In tilted states, the pressure drop was decreased as the tilted angle increased, which was associated with the reduction in liquid hold‐up. Under a roll and heave motion, it was found that the pressure drop fluctuated around the value of vertical state. Subsequently, the relative change in pressure drop was introduced to reflect the influence of sea state. It was found that the relative change in pressure drop monotonously decreased as the heave motion frequency decreased, but it could inversely increase under a low‐frequency roll motion, particularly under high liquid load with a large size Pall ring.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.173
Teacher spread0.167 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2018
Admission routes1
Has abstractyes

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