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Record W2022030977 · doi:10.5539/mas.v3n2p190

Analysis of the Flow Pipe Arrangement in RTM Process

2009· article· en· W2022030977 on OpenAlexvenueno aff
Jinliang Liu, Xiaoqing Wu

Bibliographic record

VenueModern Applied Science · 2009
Typearticle
Languageen
FieldEngineering
TopicNon-Destructive Testing Techniques
Canadian institutionsnot available
FundersTianjin Science and Technology Committee
KeywordsLaminar flowReynolds numberPipeline (software)Materials scienceFlow (mathematics)MechanicsPipe flowVolumetric flow rateFlow conditioningPhysicsMechanical engineeringEngineeringTurbulence

Abstract

fetched live from OpenAlex

In RTM process, the condition which the flow of resin in the pipeline according with the Darcy's law is the movement of laminar fluid and the Reynolds number less than 1. This paper simulated the flow of the resin in the pipeline by changing the length and diameter of the passageway of pipeline with finite element analytical method. In the result, the relationship of the fluid speed on the exit in pipeline and Reynolds number, also the scope of flow rate of the resin in the pipes can be gained. The test result shows that: exit velocity had little to do with the length, but the ratio of pipeline diameter. When the diameter of entrance assume value of 6 mm,10mm,16mm and 20mm and the diameter of exit 6 mm, 10mm and 16 mm respectively, the maximum speed should be 694.442 mm per second, 416.667 mm per second and 260.414 mm per second accordingly.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.011
GPT teacher head0.243
Teacher spread0.233 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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