MétaCan
Menu
Back to cohort
Record W571673082 · doi:10.52005/rekayasa.v4i1.150

PENGARUH HEAD DAN LUAS UNDERFLOW TERHADAP EFISIENSI PEMISAHAN SEDIMEN HYDROCYCLONE

2017· article· id· W571673082 on OpenAlexaff
Debby Rahmawati, Budi Santoso

Bibliographic record

VenueJurnal Rekayasa Teknologi Nusa Putra · 2017
Typearticle
Languageid
FieldEngineering
TopicCyclone Separators and Fluid Dynamics
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsArithmetic underflowHydrocycloneHead (geology)ChemistryEnvironmental scienceBiologyPhysicsComputer science

Abstract

fetched live from OpenAlex

Hydrocyclone adalah suatu alat yang digunakan untuk pemisahan material padat yang ada dalam medium pembawa dengan memanfaatkan efek vortex yang ditimbulkan dari gaya sentrifugal. Hydrocyclone terdiridari bagian silinder vertikal dengan bagian bawah berbentuk corong, pintu inlet pada sisi atas, pintu underflow di bagian bawah, dan pintu overflow di bagian puncak. Pada penelitian ini akan diketahui bagaimana pengaruh head dan luas underflow terhadap efisiensi pemisahan sedimen air pada alat hydrocyclone. Variasi pada efisiensi hydrocyclone sebesar 94. 1% disebabkan oleh head dan luas underflow dan sisanya sebesar 5.9% dipengaruhi oleh hal lain yang belum dapat dijelaskan oleh variabel yang ada. Antara head dan efisiensi pemisahan sedimen hydrocyclone terdapat hubungan yang searah namun lemah. Luas underflow dengan efisiensi pemisahan sedimen hydrocyclone terjadi korelasi negatif dan memiliki keeratan sangat kuat, sedangkan antara head dan luas underflow tidak terdapat hubungan. Model analisis yang paling baik dalam memprediksi variabel dependen (efisiensi pemisahan sedimen hydrocyclone) dengan adanya pengaruh variabel independen (head dan luas underflow) adalah model regresi linier berganda dengan persamaan prediksi Y=0.612 + 0.915 head – 0.646 luas underflow. Prediksi efisiensi pemisahan sedimen hydrocyclone paling tinggi yang terjadi sebesar 98. 746% dengan hasil penelitian laboratorium sebesar 99.781% yang berada pada head 50% dan luas underflow 13% dari pintuinlet.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.001

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 head0.021
GPT teacher head0.266
Teacher spread0.245 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJurnal Rekayasa Teknologi Nusa PutraSame topicCyclone Separators and Fluid DynamicsFrench-language works237,207